Title :
Unconstrained gene expression programming
Author :
Zhang, Jianwei ; Wu, Zhijian ; Wang, Zongyue ; Guo, Jinglei ; Huang, Zhangcan
Author_Institution :
State Key Lab. of Software Eng., Wuhan Univ., Wuhan
Abstract :
Many linear structured genetic programming are proposed in the past years. Gene expression programming, as a classic linear represented genetic programming, is powerful in solving problems of data mining and knowledge discovery. Constrains of gene expression programming like head-tail mechanism do contribution to the legality of chromosome. however, they impair the flexibility and adaptability of chromosome to some extend. Inspired by the diversity of chromosome arrangements in biology, an unconstrained encoded gene expression programming is proposed to overcome above constraints. In this way, the search space is enlarged; meanwhile the parallelism and the adaptability are enhanced. A group of regression and classification experiments also show that unconstrained gene expression programming performs better than classic gene expression programming.
Keywords :
data mining; genetic algorithms; data mining; knowledge discovery; linear structured genetic programming; unconstrained gene expression programming; Biological cells; Data mining; Encoding; Evolution (biology); Evolutionary computation; Gene expression; Genetic programming; Linear programming; Problem-solving; Tail;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983192