Zhengjun Pan, Lishan Kang, Jun He, and Yong Liu. An evolutionary approach to adaptive model-building. In Yao [1253], pages 236-244. * CCA 77660/95 ga95aZPan. Home/Search Document Details and Download
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An Indexed Bibliography of Genetic Algorithms in the.. - Jarmo T. Alander (2000) (Correct)
....Tack Don, 886] Han, W. G. 899] Han, Woong Gie, 901] Han, Zhangang, 354] Han, Zhenxiang, 242] Hang, Su, 434] Hansdah, R. C. 484, 492, 621] Hao, Dong, 314, 701] Haozhong, Cheng, 379] Harashima, F. 946] Harik, Georges, 626] Hasegawa, J. 840] He, Guangdong, 295] He, Jun, [146, 199] He, Lei, 307] He, Lin, 449] He, Q. H. 45, 102] He, Q. 41, 269] He, Xiangfeng, 419] He, Yao hua, 466] He, Z. Y. 164] Heeyeung, Hwang, 722] Heng, Chen, 332] Heng, E. T. H. 697, 705] Heng, Xie, 263] Heung, T. H. 104] Hewahi, N. M. 545] Hines, Evor L. 69] Ho, J. ....
....[303] Kalidindi, S. N. 634] Kalra, P. K. 635] Kalyanaraman, V. 634] Kan, Dae Seong, 895] Kandel, Abraham, 717] Kang, Byoung Ho, 868] Kang, Dae Hee, 852] Kang, Dae Seong, 950] Kang, Dong Hee, 835] Kang, Geuntaek, 800] Kang, Ki Min, 951] Kang, Lishang, 200] Kang, Lishan, [146] Kang, Li Shan, 199] Kang, Lishan, 233, 239] Kang, L. 269] Kang, M. K. 786] Kang, Myung Ju, 820] Kang, S. H. 882] Kang, Tae Won, 802, 809, 881, 894, 888] Kang, Yun Seog, 800] Kannan, J. 554, 577] Kao, C. Y. 1161] Kao, Cheng Yan, 988, 989, 991, 993, 999, 1005] Kao, ....
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Zhengjun Pan, Lishan Kang, Jun He, and Yong Liu. An evolutionary approach to adaptive model-building. In Yao [1253], pages 236-244. * CCA 77660/95 ga95aZPan.
Adaptive Parallel Algorithms From Biology - Lishan Kang Zhengjun Self-citation (Pan Kang He Liu) (Correct)
....Because of the diversity of 5 the functions during the evolution process, some of the functions generated by them may be ill posed (e.g. division by zero or logarithm of zero) in these cases,a penalty method is used to abandon them. Some test problems and experimental results presented in [8] show that our evolutionary algorithms are surprisingly effective in searching the optimal models through a quite natural representation procedure and some specific genetic operators. In comparison to traditional methods, the user does not need to know his desired model forms and parameters, both ....
Z.J.Pan, L.S.Kang, J.He and Y.Liu, An evolutionary approach to adaptive ModelBuilding, in X.Yao (Ed.), Progress in Evolutionary Computation, Lecture Notes in Artificial Intelligence, No.956, Springer-Verlag, Berlin, 236--244,1995.
Evolutionary Model-Building and Its Application in.. - Chen, Pan, Xue, Liu Self-citation (Pan Liu) (Correct)
....structure, which includes the topology of nodes and links as well as the weight values. However, it is also very difficult to design an appropriate artificial neural network structure [3] 5] Because of the limitations of the classical techniques for model building problems, Z. Pan in [4] proposed a new method based on evolutionary ideas, we call it an evolutionary model building techniques. In this method we start with a population of individuals. Each individual represents a potential solution to the problem. Through some selection ( selecting more fit individuals ) and ....
....the true situation that interpretations, predictions, and decisions would be based. The quality of a model is measured by an objective function , which is related to the discrepancy of the observed values fy i g from the expected values ff(x i )g and is normally induced by a distance function ae [4] . 2.1 Canonical GAs Genetic algorithms ( GAs ) first specified by John Holland in the early seventies, are becoming an important tool in optimization problems and machine learning. GAs are adaptive search strategies based on a highly abstract model of biological evolution. Coding techniques ....
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Z. J. Pan, L. S. Kang, J. He and Y. Liu, An Evolutionary Approach to Adaptive Model-Building,to appear in Proc. of Australian AI'94 Workshop on Evolutionary Computation.
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