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benchmark pso test system
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This a Hybrid PSO GSA Aigorithm.A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The main idea is to integrate the ability of exploitation
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Flower pollination is an intriguing process in the natural world. Its evolutionary
characteristics can be used to design new optimization algorithms. In this paper, we
propose a new algorithm, namely, flower pollination algorithm, inspired by the
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程序提出了一种基于人群混合算法，是粒子群优化和引力搜索算法的组合。主要目标提高整合PSO和GSA算法的能力-Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA)
A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization
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pso性能测试代码，实现基准的10个测试函数，通过世代距离、最大伸展、均值和方差等评估算法性能。-pso performance test code to achieve the benchmark 10-test function, through generations the maximum extension, the mean and variance peer uation algorithm performance.
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该代码为benchmark测试函数验证标准PSO算法的代码，经过测试，该代码没有问题。-The code for the benchmark test function verification standard PSO algorithm code has been tested, the code is no problem.
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在pso粒子群优化函数中的典型测试基准函数，应用检测pso算法的优劣性(In the PSO particle swarm optimization function of the typical test benchmark function, the application of PSO algorithm to check the pros and cons)
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