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References

    1. 1)
      • 1. Cohn, R.A., Lewellen, W.G., Lease, R.C., et al: ‘Individual investor risk aversion and investment portfolio composition’, J. Financ., 1975, 30, (2), pp. 605620.
    2. 2)
      • 2. Khairalla, M., Ning, X., Nashat, A.J.: ‘Modelling and optimisation of effective hybridisation model for time-series data forecasting’, J. Eng., 2018, 2, pp. 117122.
    3. 3)
      • 3. Zhou, G., Li, Y., He, Y.C., et al: ‘Artificial fish swarm based power allocation algorithm for MIMO-OFDM relay underwater acoustic communication’, IET Commun., 2018, 12, (9), pp. 10791085.
    4. 4)
      • 4. Labar, C., Garone, E., Kinnaert, M.: ‘Sub-optimal extremum seeking control for static maps’, IET Control Theory Applic., 2018, 12, pp. 745752.
    5. 5)
      • 5. Voosen, K.: ‘Machine vision algorithms that learn’, Comput. Control Eng., 2004, 15, (5), pp. 3031.
    6. 6)
      • 6. Jin, Z., Hou, Z., Yu, W., et al: ‘Target tracking approach via quantum genetic algorithm’, IET Comput. Vis., 2017, 12, pp. 241251.
    7. 7)
      • 7. Syahputra, R., Wiyagi, R.O., Suripto, S., et al: ‘A novel fuzzy approach for multi-objective optimization of distribution network configuration in complex system’, Int. J. Appl. Eng. Res., 2018, 13, (2), pp. 11201127.
    8. 8)
      • 8. Chin, Y.H., Hsieh, Y.Z., Su, M.C., et al: ‘Music emotion recognition using PSO-based fuzzy hyper-rectangular composite neural networks’, IET Signal Process., 2017, 11, (7), pp. 884891.
    9. 9)
      • 9. Al-Saud, M.S.: ‘PSO of power cable performance in complex surroundings’, IET Gener. Transm. Distrib., 2018, 12, pp. 24522461.
    10. 10)
      • 10. Syahputra, R., Soesanti, I., Ashari, M.: ‘Performance enhancement of distribution network with DG integration using modified PSO algorithm’, J. Electr. Syst., 2016, 12, (1), pp. 119.
    11. 11)
      • 11. Jiang, X., Li, S.: ‘BAS: beetle antennae search algorithm for optimization problems’, Available at https://arxiv.org/pdf/1710.10724.pdf, accessed 30 October 2017.
    12. 12)
      • 12. Eberhart, R., Kennedy, J.: ‘A new optimizer using particle swarm theory’, Micro Mach. Human Sci., 1995, 95, pp. 3943.
    13. 13)
      • 13. Solomonoff, R.J.: ‘The search for artificial intelligence’, Electron. Power, 1968, 14, (1), p. 8.
    14. 14)
      • 14. Markowitz, H.: ‘Portfolio selection’, J. Finance, 1952, 7, (1), pp. 7791.
    15. 15)
      • 15. Ge, Y., He, Y., Hu, X., et al: ‘Analysis method and empirical research on economic benefit of large-scale consumptive power grid investment’, J. Eng., 2017, 13, pp. 12851289.
    16. 16)
      • 16. Liu, J., Li, J., Wu, J., et al: ‘Global MPPT algorithm with coordinated control of PSO and INC for roof top PV array’, J. Eng., 2017, 13, pp. 778782.
    17. 17)
      • 17. Wu, H., Dong, P.: ‘PPSO method for distribution network reconfiguration considering the stochastic uncertainty of wind turbine, photovoltaic and load’, J. Eng., 2017, 13, pp. 20322036.
    18. 18)
      • 18. Mostaghim, S., Teich, J.: ‘Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO)’. Swarm Intelligence Symp., Indianapolis, USA, 2003, vol. 3, pp. 2633.
    19. 19)
      • 19. Jiang, X., Li, S.: ‘Beetle antennae search without parameter tuning (BAS-WPT) for multi-objective optimization’, Available at https://arxiv.org/pdf/1711.02395.pdf, accessed 7 November 2017.
    20. 20)
      • 20. Garg, H.: ‘A hybrid PSO-GA algorithm for constrained optimization problems’, Appl. Math. Comput., 2016, 274, pp. 292305.
    21. 21)
      • 21. Xia, X., Liu, J., Li, Y.: ‘Particle swarm optimization algorithm with reverse-learning and local-learning behavior’, J. Software, 2014, 9, (2), pp. 350357.
    22. 22)
      • 22. Xu, S., Cai, J., Wang, H.: ‘Modified particle swarm optimization algorithms based on topology and particle mutation’, Control Decis., 2018, 33, (4), pp. 111, (in Chinese).
    23. 23)
      • 23. Viswanathan, J., Grossmann, I.E.: ‘A combined penalty function and outer-approximation method for MINLP optimization’, Comput. Chem. Eng., 1990, 14, (7), pp. 769782.
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