Particle Swarm Optimization for Simultaneous Optimization of Design and Machining Tolerances

Zhou, Chen; Gao, Liang; Gao, Hai-Bing; Zan, Kun

doi:10.5772/5110

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The position of a particle is more superior if it possesses higher activeness and wider influencing range. To simulate public opinions through the particle swarm optimization, how to set the fitness function [10] is primarily necessary to solve, namely how to find the local optimal particle. In social network, the current degree of a node represents the popular and trusted degrees of this node.…”

Section: Particle Swarm Optimization and Network Public Opinionmentioning

confidence: 99%

A User-Based Modeling and Analysis of Network Public Opinion Using Particle Swarm Optimization

Kan

Rui

2013

AMR

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In the current researches on network public opinion, the events are mostly focused, instead of the users who are of great significance, but often ignored. Concerning this problem,the user-based event model encompassing the users and their concepts is introduced in this paper, and user concept clustering in spreading events is simulated with the speciation algorithm based particle swarm optimization (SPSO). According to the results of user concept clustering, the analysis of event dynamic evolution model is implemented. The clustering convergence velocity of users is controlled with the change of velocity parameter for subsequently coordinating event evolution, so that the recognition of network hot events is realized and the situation of emergencies is analyzed.Finally, the PSO-based and SPSO-based clustering behaviors of users are simulated, respectively. The experimental results show that SPSO can more effectively simulate the clustering behaviors of users in public opinion network and discover multiple user clustering centers.

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Section: Particle Swarm Optimization and Network Public Opinionmentioning

confidence: 99%