首页> 外文会议>International Conference on Artificial Intelligence and Computational Intelligence;AICI '09 >Chaotic Particle Swarm Optimization Algorithm with Niche and its Application in Cascade Hydropower Reservoirs Operation
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Chaotic Particle Swarm Optimization Algorithm with Niche and its Application in Cascade Hydropower Reservoirs Operation

机译:生态位混沌粒子群优化算法及其在梯级水库调度中的应用。

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Niche evolutionary strategy and chaotic searching were introduced into PSO, called as Chaotic Particle Swarm Optimization Algorithm with Niche (CNPSO) in this thesis. Restricted competition selection method was used to establish niche, in which each species excluded each other and dynamically formed their own searching spaces, effectively maintain the diversity of the species, so as to avoid local convergence. The chaotic searching further improved the global optimization searching precision. CNPSO was programmed to do the optimization regulation of 14 cascade hydropower stations with giant reservoirs by 48-year run-off series. With the result showing that CNPSO is highly efficient in optimization searching, capable of solving the complicated multi dimensional, strong-constraint, multi-states, multi-stages and non-linear problems such as optimization regulation of cascade hydropower stations with giant reservoirs.
机译:本文将小生境进化策略和混沌搜索引入到粒子群优化算法中,称为“小生境混沌粒子群优化算法”(CNPSO)。利用限制竞争选择法建立生态位,每个物种相互排斥,动态形成自己的搜索空间,有效地保持物种的多样性,避免局部收敛。混沌搜索进一步提高了全局优化搜索的精度。 CNPSO被编程为按48年径流序列对14个巨型水库梯级水电站进行优化调节。结果表明,CNPSO在优化搜索方面具有很高的效率,能够解决复杂的多维,强约束,多状态,多阶段和非线性的问题,例如大水库梯级水电站的优化调度。

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