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PSO topology analysis and research

Author: YangPengZuo
Tutor: TianYuLing
School: Taiyuan University of Technology
Course: Computer Software and Theory
Keywords: PSO Topology KRTG Fitness
CLC: TP301.6
Type: Master's thesis
Year: 2010
Downloads: 252
Quote: 4
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Abstract


As a new swarm intelligence methods, PSO is a very promising tool in the treatment of high-dimensional function as well as engineering design problems in the field is particularly useful. The algorithm is inspired by social psychology and artificial life, is committed to simulate social interaction between individuals, with the convergence speed, versatility and other advantages, since 1995 after being proposed has been widespread concern in the field of numerical optimization. How to accelerate the convergence speed of PSO and avoid premature convergence, has been the focus of most researchers. Measures to overcome premature convergence is mainly trying to maintain the diversity, or introduce a mechanism to escape from local minima. In accelerating the convergence rate, the main work focuses on how to choose the best algorithms. However, the majority of these researchers are pure scientific computing or engineering applications, they only focus on results rather than explore the reasons, few in-depth consideration PSO Social Psychology origin. Based on the research process, focusing algorithm theoretical analysis and experimental verification combined. For standard particle swarm optimization algorithm in the population spread too fast, easy to fall into local optimal solution defects, this paper presents a dynamic topology based KRTG particle swarm algorithm from the neighborhood structure between particles starting dynamically Adjust the topology of the population, increasing diversity of the population, the algorithm converges to the global optimal solution. Articles on PSO made a more in-depth research, focusing on the topology of particles from the particle swarm effect, made a detailed analysis and summary, try the existing PSO topology based on make some breakthroughs or improvements. Literature has demonstrated the topological structure of particle swarm algorithm performance of its great influence. Core work of this paper is to study the dynamics of a topology based KRTG particle swarm algorithm, and using K-means clustering algorithm to be optimized for its improvement. This paper first describes some of the PSO on the basics of the theory, and particle swarm theory research summarized the work; Secondly, the paper in an existing particle swarm algorithm based on the proposed dynamic topology based KRTG strategy detailed algorithm is given in the topology of the individual adaptive strategy, global update strategy and neighborhood search strategies, processes, and the use of discrete-time systems of equations apply convergence theorem, analysis and appraisal of the theoretical advantage of this algorithm and its convergence; final By solving the optimal solution of a variety of multi-dimensional functions, as well as paper PSO, IPSO with immune particle swarm optimization based on minimum theoretical WPSO algorithm World comparative experiments, the experiment proved the feasibility and effectiveness of the algorithm.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > General issues > Theories, methods > Algorithm Theory
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