[1]Granger, C. W. J., Combining forecasts- Twenty years later, Journal of Forecasting, Vol.8, pp.167-173, 1989.
[2]Krogh, A. and Vedelsby, J., Neural network ensembles, cross validation, and active learning, Ad-vances in Neural Information Processing System, Vol.7, pp.231-238, 1995.
[3]Vapnik V N. The Nature of Statistical Learning Theory [M]. New York : Springer - Verlag ,1995.
[4]Chang-Ying Ma, Sheng-yong , Yang,Hui Zhang, Ming-Li Xiang, Qi Huang, Yu-Quan Wei .Prediciton models of human plasma protein binding rate and oral bioavailability derived by using GA-CG-SVM method, Journal of Pharmaceutical and Biomedical Analysis 47(2008)677-682
[5]Vojislav, K., Learning and Soft Computing-Support Vector Machines, Neural Networks and Fuzzy Logic Models, The MIT Press, Massachusetts, 2001.
[6]Thissen, U., van Brakel, R., de Weijer, A. P., Melssen, W. J. and Buydens, L. M. C., Using support vector machines for time series prediction, Chemometrics and intelligent laboratory systems, Vol.69, pp.35-49, 2003.
[7]J.Cai,X.Ma,L.Li,H.Peng,Chaotic particle swarm optimization for economic dispatch considering the generator constraints, Energy Conversion and Management 48 (2) (2007) 645-653.
[8]P.F.Pai, C.S. Lin, A hybrid ARIMA and support machines model in stock price forcasting. OMEGA-International Journal of Management Science33,(6),(2005),497-505.
[9]LDavis,Handbook of Genetic Algorithms, Van Nostrand Reinhold,NewYork.1991.
[10]Kusum Deep, ManoJ ThakUr. A new crossover operator for real coded genetic Algorithms[J].Applied Mathematics and Computation.2006:16-19
[11]James E. Pettinger, Richhard M. Everson. Controlling genetic algorithms with reinforcement learning[C] //Proc of the genetic and evolutionary computation conference of contents. 2003, 1-11
[12]Clerc M. The swarm and the queen: Towards a deterministic and adaptive particle swarm optimization[C]. Proc of the Congress of Evolutionary Computation. Washington, 1999:1951-1957.
[13]Raghuwanshi M.M, Kakde O.G. Genetic Algorithm With Species And Sexual Selection[C] //Proc of the 2006 IEEE Conference on Cybernetics and Intelligent Systems. Bangkok, 2006, 1-8
[14]Yang Chen, JingLu Hu. Optimizing Reserve Size in Genetic Algorithm with Reserve Selection Using Reinforcement Learning[C] //Proc of the SICE Annual Conference. Takamatsu, 2007, 1341-1347
[15]Taejin Park, Ri Choe, Kwang Ryel Ryu. Adjusting Population Distance for the Dual-Population Genetic Algorithm[C] //Proc of the 20th Australian joint conference on Artificial Intelligence. Berlin Heidelberg, 2007, 171-180
[16]Jarno Martikainen, Seppo J. Ovaska. Hierarchical Two-Population Genetic Algorithm[C] //Proc of the 2005 IEEE Mid-Summer Workshop on Soft Computing in Industrial applications. Espoo, Finland, 2005, 91-98
[17]Shi Y, Eberhart R C. A modified particle swarm optimizer[R]. IEEE International Conference of Evolutionary Computation, Anchorage, Alaska, May 1998.
[18]DW van der Merwe, AP Engelbrecht. Data Clustering using Particle SwarmOptimization[J/OL]．
[19]Clerc M., Kennedy J. The particle swarm-explosion stability, and convergence in a multidimendional compiex space[J]
[20]Ebethart R.C., Shi Y. Comparing between interia weights and constriction factors in particle swarm optimization [C]//Porceedings of the Congress on Evolutionary Programming ,2000:84-88
[21]Ven den Bergh F., Engelbrecht A. P. Using Neighbourbourhoods with the Guarranteed Convergence PSO. Porceedings of the 2006 IEEE, Swarm Intelligence Symposium,2003:235-242.
[22]Angeline P.J. Using Selection to Improve particle swwarm optimization[A]. Proceedings of the 1999 Congress on Evolutionary Computation [C]. Piscataway, NJ:IEEE Press,1999:84-89
[23]Brskar S., Suganthan P. N. A Novel Concurrent particle swarm optimization [A]. Proceedings of the 2004 Congress on Evolutionary Computation [C]. Piscataway,NJ:IEEE Press,2004:792-796.
[24]Jain, A., Zongker, D. Feature selection: Evaluation, application, and small sample performance[J]. IEEE Transactons on Pattern Analysis and Machine Intelligence, 1997,19:153-158.
[25]Koller, D.Sahami, M., Toward optimal feature selection[C]. In: Proceed-ings of International Conference on Machine Learning. 1996:284-292.
[26]Kira, K., Rendell, L.A. The feature selection problem: Traditional methods and a new algorithm[C]. In: Proceedings of Ninth National Conference on Artificial Intelligence. 1992:129-134.
[27]Narendra, P.M., Fukunaga, K.A branch and bound algorithm for feature selection[J].IEEE Transactions on Computers, 1997.26(9):917-922.
[28]Iqual M. Montes de Oca MA. “An Estimation of Distribution Particle Swarm optimization Algotithm,” Springer-verlag Berlin Heidelberg, PP,72-82.2006.
[29]Shi Y, Eberhart, RC. “A modified particle sarms optimization ,” Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming, New York, PP.591-600.1998.
[30]Storn R., Price K., “Differential evolution: A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces,” Technical report, Tr-95-012, International Computer Sciences Institute, 1995
[31]A.E. Eiben,E. Marchiori, V.A. Valko, Evolutionary algorithms with on-the-fly population size adjustment , in: Proc.8th Conf. on Parallel Problem Solving from Nature, Birmingham, UK, in: Lecture Notes in Computer Science, vol.3242,Springer, Berlin,2004,pp.41-50.
[32]Osher S, Sethian J.A. Fronts propagating with curvature dependent speed: Algorithms based on the Hamilton-Jacobi formulation [J]. Journal of Computational Physics, 1988 , 79 (1): 12-49
[33]Potter M.A, De Jong K.A. A cooperative coevolutionary approach to function optimization. In: Davidor Y, Schwefel HP, Männer R,eds. Proc. of the Parallel Problem Solving from Nature—PPSN III, Int’l Conf. on Evolutionary Computation. LNCS 866, Berlin: Springer-Verlag, 1994, 249−257