Information Technology Reference
In-Depth Information
Mahmoodabadi, M. J., Taherkhorsandi, M., & Bagheri, A. (2014b). Optimal robust sliding mode
tracking control of a biped robot based on ingenious multi-objective PSO. Neurocomputing,
124, 194
-
209.
Mahmoodabadi, M. J., Taherkhorsandi, M., & Bagheri, A. (2014c). Pareto design of state
feedback tracking control of a biped robot via multiobjective PSO in comparison with sigma
method and genetic algorithms: Modified NSGAII and MATLAB
'
s toolbox. The Scientific
World Journal, 2014, 8, Article ID 303101.
Mavaddaty, S., & Ebrahimzadeh, A. (2011). Blind signals separation with genetic algorithm and
particle swarm optimization based on mutual information. Radioelectronics and Communi-
cations Systems, 54(6), 315
324.
McGookin, E. W., Murray-Smith, D. J., Li, Y., & Fossen, T. I. (2000). The optimization of a
tanker autopilot control system using genetic algorithms. Transactions of the Institute of
Measurement and Control, 22(2), 141
-
178.
Mizumoto, M. (1996). Product-sum-gravity method = fuzzy singleton-type reasoning
method = simpli
ed fuzzy reasoning method. In The Proceedings of the Fifth IEEE
International Conference on Fuzzy Systems, September 8
-
11, 1996, New Orleans
Nickabadi, A., Ebadzadeh, M. M., & Safabakhsh, R. (2012). A competitive clustering particle
swarm optimizer for dynamic optimization problems. Swarm Intelligence, 6(3), 177
-
206.
Premalatha, K., & Natarajan, A. M. (2009). Discrete PSO with GA operators for document
clustering. International Journal of Recent Trends in Engineering, 1(1), 20
-
24.
Puri, P., & Ghosh, S. (2013). A hybrid optimization approach for PI controller tuning based on
gain and phase margin specifications. Swarm and Evolutionary Computation, 8,69
-
78.
Qiao, W., Venayagamoorthy, G. K., & Harley, R. G. (2006). Design of optimal PI controllers for
doubly fed induction generators driven by wind turbines using particle swarm optimization. In
The International Joint Conference on Neural Networks, Vancouver (pp. 1982
-
1987). doi:
10.
-
Ratnaweera, A., Halgamuge, S. K., & Watson, H. C. (2004). Self-organizing hierarchical particle
swarm optimizer with time-varying acceleration coef
cient computation. IEEE Transactions
on Evolutionary Computation, 8(3), 240
255.
Ravindran, A., Ragsdell, K. M., & Reklaitis, G. V. (2006). Engineering optimization: Method and
applications (2nd ed.). New Jersey: Wiley.
Sakamoto, Y., Nagaiwa, A., Kobayasi, S., & Shinozaki, T. (1999). An optimization method of
district heating and cooling plant operation based on genetic algorithm. ASHRAE Transaction,
105, 104
-
115.
Samarghandi, H., & ElMekkawy, T. Y. (2012). A genetic algorithm and particle swarm
optimization for no-wait flow shop problem with separable setup times and makespan criterion.
The International Journal of Advanced Manufacturing Technology, 61(9
-
12), 1101
-
1114.
Sanchez, G., Villasana, M., & Strefezza, M. (2007). Multi-objective pole placement with
evolutionary algorithms. Lecture Notes in Computer Science, 4403, 417
-
427. doi:
10.1007/
-
Arumugam, M. S., Rao, M. V. C., & Palaniappan, R. (2005). New hybrid genetic operators for real
coded genetic algorithm to compute optimal control of a class of hybrid systems. Applied Soft
Computing, 6(1), 38
52.
Song, K. S., Kang, S. O., Jun, S. O., Park, H. I., Kee, J. D., Kim, K. H., et al. (2012). Aerodynamic
design optimization of rear body shapes of a sedan for drag reduction. International Journal of
Automotive Technology, 13(6), 905
-
914.
Talatahari, S., & Kaveh, A. (2007). A discrete particle swarm ant colony optimization for design of
steel frames. Asian Journal of Civil Engineering (Building and Housing), 9(6), 563
-
575.
Tang, Y., Wang, Z., & Fang, J. (2011). Controller design for synchronization of an array of
delayed neural networks using a controllable probabilistic PSO. Information Sciences, 181(20),
4715
-
4732.
Thakur, M. (2014). A new genetic algorithm for global optimization of multimodal continuous
functions. Journal of Computational Science, 5(2), 298
-
311.
-
Search WWH ::
Custom Search