Advanced Research on Computer Science and Information by Xiang Xu, Kun Zou (auth.), Gang Shen, Xiong Huang (eds.)

By Xiang Xu, Kun Zou (auth.), Gang Shen, Xiong Huang (eds.)

This two-volume set (CCIS 152 and CCIS 153) constitutes the refereed complaints of the foreign convention on laptop technological know-how and knowledge Engineering, CSIE 2011, held in Zhengzhou, China, in might 2011. The 159 revised complete papers offered in either volumes have been conscientiously reviewed and chosen from various submissions. The papers current unique study effects which are largely proper to the idea and functions of desktop technology and data Engineering and tackle a wide selection of issues akin to algorithms, automation, man made intelligence, bioinformatics, machine networks, laptop safeguard, machine imaginative and prescient, modeling and simulation, databases, info mining, e-learning, e-commerce, e-business, snapshot processing, wisdom administration, multimedia, cellular computing, normal computing, open and leading edge schooling, trend reputation, parallel computing, robotics, instant networks, and internet applications.

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Extra resources for Advanced Research on Computer Science and Information Engineering: International Conference, CSIE 2011, Zhengzhou, China, May 21-22, 2011, Proceedings, Part II

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Table 1. 5) * Limit − p gd ) do for( i =1 to number of particles) evaluate the fitness:= update f ( x) pid and pgd for d=1 to number of dimensions calculate the new velocity vid = vid + c1rand1(⋅)( pid − xid ) + c2 rand 2(⋅)( pgd − xid ) calculate the new position xid = xid + vid increase d end for increase i end for end do end 3 Experimental Settings and Simulation Strategies for Benchmark Testing Four well-known benchmark functions used in evolutionary optimization methods were used to evaluate the performance.

The concrete method is as follows: designing a migration operator, when the fitness of excellent individual among the sub-population is more than a threshold (which is called migration threshold), the excellent individual will migrate to excellent sub-population; once the individual migrated to the excellent sub-population, deleting the same individual of the original population, then checking whether there are excellent individuals in the population again. If there are, continue migrating, or else stop the migration operation.

IEEE Press, Los Alamitos (2001) 6. : A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimization. Mathematics and Computers in Simulation 68(1), 57–65 (2005) 7. : Particle swarm optimization based on swarm energy conservation. Control and Decision 25(2), 269–277 (2010) 8. : The particle swarm optimization algorithm: convergence analysis and parameter selection. Information Precessing Letters 85(6), 317–325 (2003) 9. : Minimization by Random Search Techniques.

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