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New Publications are available now online for this publication.
Please follow the links to view the publication.Real time voltage control in distribution network considering renewable energy sources
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0793
Nowadays, fossil fuels reduction, environmental impacts, transmission line and substation construction costs, economic and technical efficiency, are leading to increase distributed generation such as renewable energy sources (RES). RES are connected to distribution networks (DN), so we don't need to transmission equipment. But the reverse power flow from RES causes to change operation method. As we know weather condition have influence on output power in RES. Conventional control methods are not useful for operation and bus voltage variation damage equipment of network and customer. So we see voltage control is important in DN with RES. So developing in communicating, smart sensors and distribution network automation is made possible for real time control. In this paper we propose a real time voltage and reactive power control in distribution network considering RES. Also fuzzy sets theory is combined with partial swarm optimization algorithm to solve the multiobjective voltage control problem. (4 pages)Integrated optimization of distribution system planning and transition into new grid structures
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0744
The research project IO.Netz(*) aims to improve the current process of long term distribution system planning. Analysing and planning today's distribution systems is still characterized by isolated software tools so that network planners have to deal with a list of shortcomings. Furthermore they have to deal with an increasing complex environment and have to include additional aspects (e.g. uncertainty for the investment decisions with lower budgets; development of renewable sources). The challenge to embed decentralized renewable energy sources into the distribution network implies a tight integration of the software tool chain for planning decision support. This paper proposes to raise the synergies between the replacement strategies in asset management and investments driven by the inclusion of renewable sources. Our central approach estimates the realization probability of new decentralized generation sites, simulates grid development by a system dynamics approach, calculates investments under uncertainty and applies multi-criterial optimization based on the simulation model. (4 pages)Automatic design and optimisation of distribution systems containing renewable energy sources
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0712
This paper addresses the development of a software tool that is able to automatically design and optimise electrical distribution systems containing renewable energy sources. The tool is intended to alleviate the task of system designers and analists with regard to the integration of renewable energy sources and use of energy storage systems into their system. (4 pages)A genetic based generic filter for image impulse noise reduction
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0421
The captured images usually are influenced by impulse noise therefore removing impulse noise is one of most important pre-processing phases in many applications. In this paper, we have proposed a genetic based method to remove impulse noise. This method proposes a composite filter which is a combination of several standard filters to reduce the noise effect. The experimental results showed the proposed method could efficiently restore degraded image while it is approximately stable to noise ratio increment. (5 pages)Pattern-based guideline to empirically analyse software development processes
http://dl-live.theiet.org/content/conferences/10.1049/ic.2012.0017
Background: Little is yet known about how to qualitatively analyse development processes to steer their further optimisation. Thereby, companies are often left to the expertise of third parties when performing such an analysis. Aim: We aim at elaborating a way of empirically analysing development processes on basis of 9 empirical studies we performed at our research group. Method: We analyse 9 empirical studies for commonalities in their research objectives, research methodologies, cases, and methods used to infer a set of research methodology patterns. Results: We discover and discuss three methodology patterns, which we embed into a first experience-based guideline to conduct qualitative analyses of development processes. Conclusion: Our guideline is inferred from a series of successful studies. However, since qualitative analyses always will depend on many aspects that cannot be standardised, we lay with this contribution a first, but fundamental step to be further discussed, evaluated, and extended.A novel method for tuning the PID parameters based on the modified biogeography-based optimization for hydraulic servo control system
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0171
PID control is used widely in hydraulic servo control system. The PID control parameters are very important to performance of hydraulic servo control system and how to find rapidly the optimum values of PID control parameters is a very difficult problem. Based on Matlab/simulink software and taking the IATE standards of the optimization design as objective function, a global search optimization method with the modified Biogeography-Based optimization (MBBO) was applied for the optimization of the three parameters of PID controller of electric-hydraulic servo system of parallel platform. Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. In this paper, a modified version of the BBO is proposed to improve its convergence. The MBBO is used to deal with the PID Controller tuning. Simulation results show that the proposed parameter optimum method is an effective tuning strategy and has good performance compared with adopted NN network optimization method. (5 pages)Improved maximum power extraction strategy for PMSG based wind energy conversion system
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0325
Even though hill climbing search (HCS) control is the simplest MPPT algorithm that does not require any prior knowledge of the system, it has the disadvantage of being slow in its response. This slowness in the response is due to the number of perturbations involved in climbing the hill and the settling time of the each perturbation. This paper proposes an improved HCS control, in which the nature of the input perturbation is changed, so as to improve the control algorithm's response speed in tracking the maximum power point of a wind turbine. (6 pages)Coordinated optimization among multi-cycle generation schedules
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0110
Generation schedule optimization means scheduling unit commitment, economic dispatch and auxiliary service of generators to minimize total cost for specified time scope by considering system balance constraints, generator operation constraints, grid security constraints, energy saving and emission reduction constraints. Generation schedule optimization is a continuous promoting procedure. In order to coordinate multi-cycle generation schedule optimization for yearly energy contract tracing dispatch mode, this paper presents a continuous generation schedule optimization infrastructure. The longer cycle generation schedule provide direction for shorter cycle generation schedule optimization. Then shorter cycle optimize generation schedule aimed at minimized difference with generation schedule derived from last longer cycle optimization considering latest forecast and grid operation information. As to eliminate the random power bias distribution among generators, four bias minimization objectives, which include sum-bias, sum-cost, minimized max-bias and minimized max-cost, and four relevant bias evaluation indexes are defined. Example analysis indicates that sum-cost function is most suitable for coordinated optimization among multi-cycle generation schedule optimization. Finally, a practical cooperation method between real time generation schedule and automatic generation control (AGC) is presented. Through the comparison between current output and next period generation schedule, the AGC program could determine whether participating in current ACE adjustment or not, and calculate adjustment magnitude. Application of the coordinated optimization among multicycle generation schedules could implement continuous optimization of generation schedule and loop control of generator. (5 pages)Observer based state feedback controller design for pseudo direct drive<sup xmlns="http://pub2web.metastore.ingenta.com/ns/">®</sup> using genetic algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0263
The paper describes a technique, based on a genetic algorithm GA, for the design and tuning of a state feedback controller with a reduced order observer, for a Pseudo Direct Drive Permanent Magnet Machine PDD. The controller was designed to eliminate torsional oscillations caused by the low stiffness of the magnetic gear, and provide smooth transient and good speed tracking based on ITAE performance index. (6 pages)Hybrid excitation synchronous machine control in electric vehicle application with copper losses minimization
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0252
This paper presents an optimal current control for the hybrid excitation synchronous motor in electric vehicle application. The control aims to meet the torque and speed requirements while insuring minimal copper losses. Extended Lagrange multipliers optimization method (Kuhn-Tucker conditions) is used to elaborate analytical expressions for the optimal reference armature currents as well as for the field current if with respect to armature current and voltage constraints. Simulation over the new European driving cycle proves that the proposed optimal control leads to the lowest copper losses compared to the results obtained by any other commonly used synchronous motor control strategy. (6 pages)High frequency fault location method for transmission lines based on artificial neural network and genetic algorithm using current signals only
http://dl-live.theiet.org/content/conferences/10.1049/cp.2012.0041
The present transmission systems are rapidly changing principally due to an increasing demand for better utilisation of existing lines resulting in lower transient stability limits, and also due to an increase in the complexity of the networks with small-scale distributed generation being connected into the existing networks. The current protection/fault location techniques are not conducive to such networks. This paper investigates a novel fault location method based on current signals only and utilising Artificial Intelligence technology. Importantly, the robustness and sensitivity of the technique developed is presented through an extensive series of studies and results when applied to complex power networks. (6 pages)Stigmergic search for a lost target in wilderness
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0168
The problem of searching for a missing person in a wilderness search and rescue application is often modelled as a straightforward application of Bayes' Rule to a conventional occupancy grid. However, this model fails to exploit many potentially valuable secondary cues - such as material dropped by the missing person or unmarked tracks - which could aid in the search process. In this paper, we develop a Bayesian approach to exploit this secondary evidence. Our approach is inspired by the stigmergic approach to indirect coordination: evidence left by the missing person on the ground is used to coordinate the actions with the searching UAV. To achieve this coordination, we compute the joint probability over multiple cells using a path-base representation of the missing person trajectory. The trajectory is modelled using an agent-based simulation. As new evidence becomes available, a resampling scheme is used to update the ensemble of paths. We demonstrate the performance of the algorithm in a simple search scenario, and show a significant improvement over current search methods. (5 pages)Coastline detection using coupled variational level-set formulation
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0107
In this paper, we describe a method of detecting dynamic coast-lines from ground-level images using an integrated level-set framework. A dynamic coastline is represented as the longest boundary of intersection of multiple moving fronts (geometric active contours) corresponding to multiple regions within the image together with model of their evolution using the level set formulation. The evolution of the various moving front is modelled using an adaptive variational formulation of the level set function that in-turn minimizes an appropriate energy function. We explore the performance of the model and show that the proposed method achieves better accuracy than other widely used methods for coastline extraction. (6 pages)Evaluating iris segmentation for scenario optimisation
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0098
Iris recognition is a biometric modality which offers the potential for high accuracy and, increasingly, for application in more diverse environments than hitherto. Poor segmentation is one of the most important factors likely to compromise iris recognition performance. Hence, research in the area of iris biometrics has often been focused on efforts to enhance the performance of iris segmentation techniques, and this has led to considerable work on iris segmentation. This paper presents a detailed investigation, evaluation and comparison of several segmentation approaches (including a new algorithm proposed by the authors) proposed in the literature based on their accuracy and processing speed. To be consistent with the research of others, for all quantitative experiments, algorithms have been evaluated on two iris databases, namely CASIA V1.0 and a subset of the BioSecure database. (6 pages)Self-dependent 3D face rotational alignment using the nose region
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0101
One of the challenging issues for 3D face recognition is face alignment. Many alignment algorithms are computationally expensive, making them unsuitable for real-time biometrics, or not robust enough to detect large variations in pose. In this work, a novel algorithm for 3D face rotational alignment is proposed, that uses the nose region. After preprocessing and nose region identification, alignment is performed by applying two energy functions to the nose footprint, identified as the largest filled region in the inverted depth map. These functions are minimised using Simulated Annealing and the Levenberg-Marqurdt algorithm. The energy minimisation and segmentation procedures continue iteratively until a stopping criterion is met. The method has been applied to images from the Face Recognition Grand Challenge (FRGC) v2 dataset and the consistency of its alignment has been verified using the iterative closest point (ICP) algorithm. As a self-dependent algorithm, it does not require a pre-aligned image as a reference and also has a high computational speed, approximately three times faster than the brute force ICP technique. (6 pages)A dynamic resource allocation model along with adaptive power control in a multi-rate direct sequence CDMA with MIMO
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0074
A throughput maximization algorithm for a CDMA system comprising of variable bit rate (VBR) groups has been proposed. The algorithm is aimed at efficiently utilizing the radio resources for maximal throughput while meeting the minimum data transmission rate and Quality of Service (QoS) requirements of each user group. The power of each group is also dynamically controlled so as to minimize the cell interference thereby maximizing the system capacity. The model also predicts the reduction in effective cell radius because of cell breathing under Gaussian noise and a Rayleigh faded channel. The simulation of multiple input multiple output (MIMO) antenna in such a system reports an improvement in the Bit Error Rate (BER) performance of the system by up to 80%. The allocation scheme efficiently utilizes as much as 99.9% of the available bandwidth in the system.Estimation of 3D head region using gait motion for surveillance video
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0105
Detecting and recognizing people is important in surveillance. Many detection approaches use local information, such as pattern and colour, which can lead to constraints on application such as changes in illumination, low resolution, and camera view point. In this paper we propose a novel method for estimating the 3D head region based on analysing the gait motion derived from the video provided by a single camera. Generally, when a person walks there is known head movement in the vertical direction, regardless of the walking direction. Using this characteristic the gait period is detected using wavelet decomposition and the heel strike position is calculated in 3D space. Then, a 3D gait trajectory model is constructed by non-linear optimization. We evaluate our new approach using the CAVIAR database and show that we can indeed determine the head region to good effect. The contributions of this research include the first use of detecting a face region by using human gait and which has fewer application constraints than many previous approaches. (6 pages)A new technique to solve minimum spanning tree (MST) problem using modified shuffled frog-leaping algorithm (MSFLA) with GA cross-over
http://dl-live.theiet.org/content/conferences/10.1049/ic.2011.0046
A minimum spanning tree (MST) of a connected, weighted (non-negative), undirected graph G = (V,E) is such that vertices of the graph G is connected by edges which have minimum weight and it forms a tree. Finding the MST from a graph is a NP-hard problem. In this paper a new technique is proposed to solve MST problem using Modified Shuffled Frog- Leaping Algorithm (MSFLA) with Genetic Algorithm (GA) cross-over. SFLA is a meta-heuristic search method inspired by natural memetics. It combines the benefits of both meme-based Memetic Algorithm (MA) and social behaviour based Particle Swarm Optimization (PSO). In this paper some modification of SFLA is done and applied it to MST problem. Extensive experimental results show that the algorithm performs very well compare to other algorithms and gives accurate results with minimum no of iterations.Pro-active energy management for Wide Area Networks
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0682
We present a methodology for achieving energy savings in excess of 30% in Wide Area Networks. The approach applies a limited set of pre-calculated network topology configurations derived via a Genetic Algorithm across the day. The GA determines the minimum set of resources required in order to support a given traffic demand. Information gleaned from SNMP trap messages, triggered by the use of a link utilization threshold, determine when to switch between configurations. The threshold employs moving average smoothing and is discretely readjusted over the course of a daily cycle based on anticipated basal load variations. By exploiting MT-OSPF this approach provides a scalable and flexible means of reconfiguring an infrastructure that avoids routing discontinuities, excessive computational effort and the exchange of considerable volumes of control information.Research and realization on the ant colony optimization algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0894
This is where the abstract should be placed. It should consist of one paragraph and a concise summary of the material discussed in the article below. It is preferable not to use footnotes in the abstract or the title. The acknowledgement for funding organisations etc. is placed in a separate section at the end of the text. We wish you success with the preparation of your manuscript. The ant colony algorithm (ACA ) is a simulated evolutionary algorithm , which is inspired by real ants foraging in natural world. In this paper, it has effectively solved the problem of precocity and halting of the ant colony algorithm, taking use of the global and rapidity of the PSO. Meanwhile, it can also judge the standard of the route by use of the eliminating- cross. Through classic experiments about Traveling Salesman Problem, the optimization algorithm has the better astringency, robustness and efficiency.The Voronoi-Delaunay dual diagram: mesh generation and cosmetics
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0024
The weighted Voronoi diagram has been developed to improve the overall quality of the resulting Voronoi-Delaunay dual diagram. Several optimization techniques have also been studied and compared in this work, which includes the direction search, particle swarm optimization and the new metaheuristic optimization algorithm Cuckoo Search. Numerical results show that these optimization techniques can play an important role in reducing the number of bad elements with CVT reinsert loop.Study on bi-level programming model of highway traffic network based on the sustainable development theory
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1376
The large-scale highway construction can cause certain influence for environment while satisfying traffic demand. Based on the idea of sustainable development, the tradition one-goal layout optimization model of city highway network is extended. The lower-level model is the stochastic user equilibrium assignment, then according to goals about the economy, society, environment and energy sustainable development, highway traffic network bi-level programming model is established, and the simulation annealing algorithm is designed. This model not only can satisfy the traffic demands, but can also satisfy the goals of the sustainable development.Resource search optimization of P2P based on ISP and resource character
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0725
Although the exited unstructured P2P resource search algorithm can enhance the performance of resource searching, but it will generate lot of P2P traffic and will consume a huge network bandwidth. Consider the messages of Internet service provider (ISP) and the clustering of P2P networks, the article proposed an on-demand resource search algorithm which based on the ISP and the similarity of resource character. In process of searching resource, the algorithm first selects the nodes which are in the same ISP and the character similarity of which and search message are greater than a certain threshold to forward searching message, so traffic is controlled in a same ISP network maximized, thus the load of the backbone network and network egress is reduced. Simultaneously, make on-demand search in the searching process according to the numbers of user-needed resources. Experimental results show that the algorithm can effectively improve the performance of resource search and reduce the consumption of bandwidth.Mapping the virtual networks with stochastic bandwidth resource request in multi-datacenters
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1464
Network virtualization allows the design of multiple diverse virtual overlay network architectures over a common physical infrastructure. A key issue in designing such virtual networks (VN) is the mapping of the VN onto the underlying substrate network. Accordingly, many research works have focused on the VN mapping problem. However, these works only consider the case where the VNs require deterministic amount of network resources. Some other works even deal with the dynamic resource demand by using over provisioning, which is simple but inefficient. In this paper, we investigate the online stochastic VN mapping (StoVNM) problem in multi-datacenters, in which the VN requests follow a Poisson distribution and the associate VN bandwidth demands follow a Normal distribution. We formulate the StoVNM problem as an optimization problem with the objective of minimizing mapping cost and load-balancing. Since the VN mapping problem is NP-hard we devise a sliding window technique based on heuristic algorithm w-StoVNM for tackling this NP-hard problem efficiently. Through extensive simulations we demonstrate the effectiveness of the proposed approach compared to traditional VN mapping solutions in terms of VN mapping cost, blocking ratio and total net revenue in the long term.Comparison of various mutation schemes of differential evolution algorithm for the design of low pass FIR filter
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0477
Differential Evolution (DE) has established itself as a very useful tool in the domain of optimization technique in recent times. It has found its paramount importance in various signal processing applications. Amongst them, design of Finite duration Impulse Response (FIR) filter using DE algorithm has drawn special interest in recent times. In this paper, we have analyzed the impact of various mutation strategies of DE algorithm for the design of linear-phase low pass FIR filter. The performance of this evolutionary optimization technique has been evaluated in terms of its convergence behaviour for different mutation schemes. Additionally, the behaviour of the designed filter under different mutation strategies has been analyzed by studying its magnitude and impulse response. Finally, the most suitable mutation scheme has been suggested for this specific design problem.Modelling and optimization of renewable energy integration in buildings
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0345
The sustainable security of energy supply, led both developed and developing countries to make and implement new policies to improve efficiency in energy consumption, to adopt new alternatives like renewable energy systems. To face the economic, social, technological and environmental challenges, the need for energy conservation as well as for developing renewable technologies has become even more critical. Hybrid systems can be considered as a reasonable solution, capable to support systems that cover the energy demands of both stand-alone and grid connected consumers. Commonly, it consists of a mix of two or more energy sources used jointly to provide increased system efficiency as well as greater balance in energy supply. The aim of this paper is to present the architecture of a Decision Support System (DSS) that can be used for the hourly energy management of a mix of renewable energy systems. Specifically, an integrated model representing a hybrid energy generation system (characterized by solar plate collector, PV, wind and battery storage) connected to the grid is developed. The approach is based on mathematical modelling of each component, then an optimization problem is solved in order to better manage and control the energy flow so to ensure reliable supply of demand.Online traffic engineering by optimizing inbound traffic in locator/identifier separation context
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1495
To cope with the scalability issue of current Internet inter-domain routing system, several proposals addressing identifier and locator separation are proposed recently. LISP is one of them. In a LISP-capable network, when end-system identifier (EID) is not routable, a mapping system must map an EID to a routing locator (RLOC). By optimizing EID-RLOC Mapping Assignment (ERMA) for an AS, inbound traffic can be optimally distributed in the AS. In this paper, ERMA optimization problem is studied. We introduced an online ERMAO scheme based on delay information of probe packets. Simulation results show that online optimizing ERMA can achieve better network performance, e.g., lower packet delay and maximum link utilization.Bootstrapping neural network regression model for motor drive vibration optimization through genetic algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0074
This work proposes an optimization procedure based on a bootstrapped neural network interpolation approach and the Genetic Algorithm method. The bootstrapped neural network is used to generate designed data sets in order to estimate a mapping from input to output space in an intrinsic experiment in a motor drive vibration study. The optimization procedure is aimed to minimize the motor vibration by adjusting some drive control parameters.Analysis on the mechanism and optimization method of urban traffic structure
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1388
Most cities in China have moved into a fast developing stage of motorization, and traffic jam is one of the most serious problems following it. Controlling and utilization traffic structure are particularly important in this special period. Firstly, the definitions of urban traffic structure, resident traveling efficiency and traffic structure utilization are given. In particular, to be more reasonable, the traditional definition of traffic structure is extended in this part. Then the mechanism of urban traffic structure is provided with the analysis on the relationship among utilization of urban transportation structure, improving the efficiency of urban residents traveling and alleviating urban traffic jams. Next, the paper puts emphasis on discussing methods of utilization traffic structure and traffic demand management, and time/space control are developed in this part, and the method of time/space control is provided on the basis of the extended definition of urban traffic structure.Research on the 3G mobile network optimization
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0703
Based on the actual operation of the system and QoS status, the 3G mobile network optimization consists of system dynamic testing, analysis and adjustment to the existing system configuration to provide the highest QoS, the optimum coverage and the lowest network cost-effective. Capacity planning and pilot pollution are two of the key issues in CDMA network optimization. By coverage optimization, power control, access control, network capacity can be improved. And eliminating RF pollution by parameters adjustment can furtherly improve performance of CDMA network.WSN nodes deployment based on artificial fish school algorithm for traffic monitoring system
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0320
To deal with the optimizing deployment problem of sensor network nodes for Traffic Monitoring System, we use a comprehensive evaluation function to evaluate the performance of the sensor network nodes deployment, and develop a optimization model which take some factors into account, such as the scope of monitoring, communication range etc. The optimization program based on artificial fish school algorithm is proposed to solve this problem. In the simulation experiment, we use a simplified road grid map, and the results show that compared with initial manual deployment, artificial fish school algorithm improved the nodes deployment of wireless sensor network for Traffic Monitoring System. (5 pages)Research on ant system with taboo rules and its applications in VRPDP problem
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1486
The traditional ant algorithm is a swarm intelligence optimization algorithm which has many good features when solving combinatorial optimization problems such as TSP. But it has the limitations of stagnation and poor convergence, and is easy to fall in local optima, which are the bottlenecks of its wide application. This paper puts the taboo rules into the ant algorithm. The simulation experimentation result shows that the TAS algorithm brought up in this paper has good performance in convergence speed and steadiness. In addition the simulation results shows that this algorithm brought by this paper can get a better solution when solving VRPDP.Novel selection factors based optimal placement of TCSC controller in power transmission system for contingencies using PSO
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0388
It is essential for the Power Managers to study the impact of contingencies on system security and to identify the best ways to improve the system security by proper use of FACTS controllers in the Power System Network. This paper presents three different selection factors to decide the best location to place TCSC in order to improve the system security under contingencies. The particle swarm optimization algorithm is utilized for finding the settings of the TCSC to be placed on the line selected based on the three factors. The optimization gives the solution of TCSC settings with the objective of minimizing the severity of overloading of the system for the considered contingencies. The proposed approach is examined and tested on IEEE 6 bus system and also tested in Indian Power Utility Network supplying to major metropolitan city.A modified form of mutation for genetic-fuzzy classifier design
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0490
This paper presents a Genetic Algorithm (GA) approach to obtain the optimal rule set and the membership function. While designing the fuzzy classifier using GA, the membership functions are represented as real numbers and the rule set is represented by the binary string. BLX-a crossover is used for real numbers and two point crossover and an advanced operator called gene cross swap operator are used for the binary string. A modified form of mutation that uses the concept of velocity updating in Particle Swarm Optimization (PSO) is proposed to improve the convergence speed and quality of the solution. The performance of the proposed approach is evaluated through development of fuzzy classifier for four standard data sets. Simulation results show that the proposed algorithm produces a fuzzy classifier with minimum number of rules and high classification accuracy.A novel self-adaptive differential evolution algorithm for efficient design of multiplier-less low-pass FIR filter
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0460
Variety of real-world optimization problems can be successfully solved by employing a powerful technique, called Differential Evolution (DE) algorithm. The popularity of DE has grown tremendously since its inception as it includes a very few number of control parameters. However, the selection or tuning of these parameters plays a crucial role in determining the performance of the algorithm in terms of its convergence behaviour. In this paper, a novel Self-Adaptive DE (SADE) approach has been proposed for the de sign of a multiplier-less low-pass linear-phase FIR filter to improve the computational efficiency of the algorithm. For this purpose, the convergence behaviour of the SADE technique has been presented and it has been compared with that of traditional DE technique. Additionally, the performance of the SADE-optimized filter has been evaluated in terms of its magnitude response. The corresponding magnitude response for the DE-optimized filter has also been presented for comparison. It has been established that the proposed SADE algorithm outperforms the traditional DEfor this particular design problem.Research on mixed set programming for aircraft schedule recovery
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1371
Bad weather and aircraft failure are often the causes that the airline's flight schedule cannot be processed as planned. Aircraft Schedule Recovery problem is a typical NP-Hard problem. Different from Mixed Integer Programming, this -research proposes a Mixed Set Programming method to solve the problem by building a Natural Constraint Language model and designing efficient search rules. Instances of different scales are tested respectively using the Greedy Simulated Annealing Algorithm and MSP to analyze the feasibility of the MSP method in solution quality and time efficiency.Coupling field analysis and non-deterministic optimization by means of multiprocessor parallel computation for characterizing magnetic anisotropy
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0093
The paper proposes an automated procedure for linking an identification algorithm implemented in a general purpose environment (MatLab™) with a commercial Finite-Element code for magnetic field analysis (VF Opera™). This procedure is applied to identify automatically the B-H curve of anisotropic magnetic laminations in the direction normal to the sheet surface. A multiprocessor computer made it possible to perform parallel computations. An identification procedure based on a non-deterministic algorithm allows finding the whole B-H curve for sheet samples.PQ events classification and detection - a survey
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0412
This paper carries out a comprehensive review of various techniques used in the recent years in PQ event classification. Within this context, artificial intelligence and optimization techniques as well as their fusion have been reviewed in the field of PQ. The important techniques used in past are also provided in tabular form. Although this review cannot be collectively exhaustive, it may be considered as a valuable guide for researchers who are interested in the domain of PQ and wish to explore the opportunities offered by these techniques for further improvement in the same field. It is also analysed that still more research is to be done for online analysis of PQ events.Research on application of fish swarm behaviour in intelligent transportation system
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1403
Intelligent transportation system (ITS) is a hot issue that makes many countries intensify efforts in research of the area, the solutions for some traffic problems, such as, congestion or traffic safety are improved by the ITS. Intelligent driving assistance system which is one important branch in ITS, is wildly used in modern vehicles, but these devices are only based on one single car. It is well known that fish school shows perfect swarm behavior which is widely considered as a typical example of self-organized grouping in which fish individuals perform a unified collective action. In this paper, the theory of fish school is applied to ITS. We use an improved artificial potential field to construct the model of fish group behavior, under some certain constraints. We propose a novel concept for multi vehicles travel coordinative control law inspired by fish group behavior, by which makes the cars motion with unified collective action and reinforce the ability of active safety and traffic capacity. In order to illustrate the validity of the strategy, the algorithm is applied in two typical traffic problems: the traffic bottleneck and the obstacle avoidance, and the simulation results show the validity and the feasibility of this idea.Evaluation and optimization of bus route network in Wuhan China
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1392
With the expansion of urban area, urban bus transit plays an increasing important role in urban transportation. Nowadays, factors for bus route network planning become increasingly complicated with the construction of rail transit in metropolises of China. The object of this research is to optimize bus network in Wuhan using a GIS-based framework to alleviate or solve the problems exposed from current existing bus routes in the city, such as reducing the route overlapping, enlarging the network coverage, and reducing the nonlinear coefficient. This research employs a method for multi-modal transit route design based on stops, which treats certain rail routes as restrictions. Genetic algorithm (GA) is applied to search for optimal combination of candidate routes. With the case of central area in Wuhan, a scenario has been developed for the short-term situation with No.1, 2 and 4 rail routes. A comparison is made between the existing and the optimized results. It has been found that our GIS-based optimization approach may generate more appropriate bus route network for the large city.A new method of parameters optimization based on self-calling SVR
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1452
Parameters optimization selection is a key point in Support Vector Regression (SVR). Exhaustive search spends a lot of time, especially when large-scale samples need to be trained. A new method based on Parameters Subsection Selection and Self-Calling (PSS-SC) SVR is proposed. First of all, parameters optimization selection involves in penalty coefficient c, kernel parameter g and non-sensitive coefficient p, and the combination (c,g,p) will make a great effect on the prediction accuracy of SVR. The proposed method is used to select the optimal parameter combination with less time to achieve the better performance of SVR. Firstly, trisection is adopted according to the span of each parameter, thus, three medians as test points could be available for each parameter. Totally 27 parameter combinations (c,g,p) and MSEs of corresponding SVRs could be achieved. Then the mapping relationship between the 27 combinations (c,g,p) and their MSEs could be established. And then, the MSEs of the remaining parameter combinations could be conducted with the mapping relationship. Thus, the N parameters combinations corresponding to the first N minimum MSEs are selected as the candidates TOP-N. Finally, the TOP-N combinations (c,g,p) are applied to SVR to achieve their MSEs separately. The minimum MSE corresponds to the best parameter combination. Experiments on 5 benchmark datasets illustrate that the new method not only can assure the prediction precision but also can reduce training time extremely.Probability density function estimation based on representative data samples
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0757
The relationship between the results of probability density function (PDF) estimation based on Parzen windows method and the number of observed samples is demonstrated in this paper. Based on the experimental analysis, we get that the increase of observed samples may not bring about the obvious improvement of estimated result. Then, the strategy by using the representative data samples to estimate PDF is proposed. The representative data samples are selected from the original dataset by considering Entropy-Maximization and Distance-Minimization (EMDM). Finally, the experimental results on the artificial datasets shows that the estimations of PDF by using the representative data samples can obtain the similar levels of error performance compared with the estimations on the whole dataset.Minimum vertex cover problem based on ant colony algorithm
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1389
By applying Ant-Cycle model of Ant Colony Algorithm, and modifying the state transition probability, an approximation algorithm is obtained for the minimum vertex cover problem. The time complex of the algorithm is O(n<sup xmlns="http://pub2web.metastore.ingenta.com/ns/">2</sup>) , where n is the number of vertices in a network. In the end, an example is given to illustrate the process of the algorithm.Improving feature extraction in keystroke dynamics using optimization techniques and neural network
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0493
This paper presents a novel application of optimization technique to user identity authentication using keystroke dynamics. Keystroke dynamics is a biometric technique to identify a user based on the analysis of his/her typing rhythm. Mean, Median and Standard deviation of feature values such as Latency, Duration and Digraph are measured and compared the performance. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used to select the subset of the features extracted and Neural Net is used for classification. Particle Swarm Optimization gives moderate performance than Genetic Algorithm with regard to feature reduction rate. Digraph with median as the feature gives good result when compared with other features.The ant colony optimization algorithm for web services composition on preference ontology
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1455
The Optimization Algorithm for Web Services Composition on Preference Ontology (OAWSCP) is put forward. OAWSCP, which makes some improvements on primary ACO (Ant Colony Optimization), builds simulation model based on services composition, and sets multiple pheromones and pheromone weights to denote the preference to different properties of a service. The algorithm can also simulate the instability of the flow of services composition, and react according to the flow change of the services composition. The algorithm can also detect if the optimizing is converging to local optimization findings, and in this case the algorithm can take measures to change its direction, and as a result reduce the probability of the algorithm to converge to local optimization findings. In order to verify the feasibility of the algorithm, the paper also builds simulation application system. The result of the performance test proves that the algorithm is more effective than primary ACO.A new framework to design distributed query system
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1471
This paper proposes a new framework to design query systems which could be used in DNS systems. An efficient ILP model, which is able to take network layer information into count, is formulated to design such query systems. By simulation, we demonstrate that query system in our framework can relax unnecessary constraint and trade off between query delay and storage cost.A study on personalized recommender system in e-commerce based on ant colony
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1445
This paper proposed the combination of existing Ant Colony Algorithm and the recommendation algorithm. And it introduced the concept of pheromones and volatile in Ant Colony Algorithm. Combines the browsing behavior and the preferences of similar user in recommended process, and calculate the score of each page. And proposed the solutions of specific problems when the algorithm applying in recommender system.Optimal placement of capacitor in radial distribution system using PSO
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.0383
The problem of capacitor allocation in Electric Distribution Systems involves maximizing energy and peak power loss reductions by means of capacitor installations. This paper presents a novel approach using approximate reasoning to determine system candidate nodes in a distribution system for capacitor placement. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two the Particle Swarm Optimization Technique is used to identify the sizes of the capacitor for minimizing the energy loss cost and capacitor cost. The proposed method is applied to 15bus and 33bus radial distribution system.Optimization design and fracture analysis of shift fork shaft of the transmission
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1033
Taking the shift fork shaft of transmission as research object, through analyzing the position and shape of the fracture on shift fork shaft, the paper gives the optional design scheme of shift fork shaft. The three dimensional mathematical model of the optimized shift fork shaft is set up by use of Pro/E software and the finite element analysis is carried out by ANSYS Workbench software. The analysis results show the strength of the optimized shift fork shaft can meet the design requirement.A new parameter optimization algorithm of SVM
http://dl-live.theiet.org/content/conferences/10.1049/cp.2011.1451
The proper selection of parameters, i.e. RBF kernel parameter g, penalty factor c, non-sensitive coefficient ɛ of SVM model can optimize the performance of Supporting Vector Machine (SVM). The most commonly used approach is grid search. However, when the data set is large, a terribly long time will be introduced. In order to reduce the selection time of optimal parameters, we propose a new heuristic search algorithm (HS-SVM). The proposed algorithm firstly finds the parameter combinations (c, g) with N minimum MSEs by setting randomly constant ɛ .The N selected (c, g)pairs are integrated with all possible ɛ to do cross-validation to get parameter combination (c, g, ɛ) with minimum MSE. The corresponding parameter ɛ is regarded as the best. Then this ɛ is combined with the prior N combinations (c, g) to do the cross-validation of SVM. The parameter combination with minimum MSE is the optimal. Experiments show that the proposed algorithm is more efficient than the gird search.