By Fengrui Wang, Wenhong Wang, Quanke Pan, Fengchao Zuo (auth.), Zhihua Cai, Zhenhua Li, Zhuo Kang, Yong Liu (eds.)

ISBN-10: 3642048420

ISBN-13: 9783642048425

ISBN-10: 3642048439

ISBN-13: 9783642048432

Volumes CCIS fifty one and LNCS 5812 represent the lawsuits of the Fourth Interational Symposium on Intelligence Computation and functions, ISICA 2009, held in Huangshi, China, in the course of October 23-25.

ISICA 2009 attracted over three hundred submissions. via rigorous stories, fifty eight papers have been integrated in LNCS 5821,and fifty four papers have been accumulated in CCIS fifty one. ISICA meetings are one of many first sequence of overseas meetings on computational intelligence that mix components of studying, edition, evolution and fuzzy common sense to create courses as substitute strategies to man made intelligence.

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Extra resources for Advances in Computation and Intelligence: 4th International Symposium, ISICA 2009 Huangshi, China, Ocotober 23-25, 2009 Proceedings

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Thus the individuals can analysis the tendency of stock price movement in long, middle and short term. In this way the disturbance from noise in trade market was avoided. It makes predication more accurate. In the evolve process the best individual will be selected and survive to the next generation. The remaining normal majority will be replaced by offspring. The genome is an integer string, with Table 1 providing an overview of each genes meaning. The mutation operation changes the time duration, time scale and weight.

Biol. : Finding functional sequence elements by multiple local alignment. : A profile-based deterministic sequential Monte Carlo algorithm for motif discovery. : Identifying DNA and protein patterns with statistically significant alignments of multiple sequences. : GAME: detecting cis-regulatory elements using a genetic algorithm. : TFBS identification based on genetic algorithm with combined representations and adapbive post-processing. : Detection of functional DNA motifs via statistical over-representation.

Factors include the size of the global data set, the maximum amount of local data that blocks of threads can share, the number of thread processors in the GPU, and the sizes of the on-chip local memories. In summary, Graphics Processor Unit’s advantages of highspeed, unique compute architecture, easy implementation, inexpensive, will make evolution computing become increasing common. References 1. : A Survey of Parallel Genetic Algorithms (1998) 2. : A Survey of General-Purpose Computation on Graphics Hardware,STAR – State of The Art Report (2007) 3.

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Advances in Computation and Intelligence: 4th International Symposium, ISICA 2009 Huangshi, China, Ocotober 23-25, 2009 Proceedings by Fengrui Wang, Wenhong Wang, Quanke Pan, Fengchao Zuo (auth.), Zhihua Cai, Zhenhua Li, Zhuo Kang, Yong Liu (eds.)


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