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Development and analysis of a modified Artificial Fish Swarm Algorithm

机译:改进的人工鱼群算法的开发与分析

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The analytical development and simulation of a modified Artificial Fish Swarm Algorithm is presented in this paper. It addresses the problem of the conventional AFSA migration into the local minima due to the constant effects of its control parameters such as the visual distance and step size. An iterative behavior was introduced such that each generation can select its guiding parameters adaptively. The performance of the modified algorithm was evaluated using a subset of applied mathematical optimization test functions namely Ackley, Cosine Mixture, Neumaier, Rosenbrock and Rastragin. Results show that the modified algorithm performed better in four (4) out of the 5 test functions.
机译:本文介绍了一种改进的人工鱼群算法的分析开发和仿真。它解决了常规AFSA由于其控制参数(例如视距和步长)的恒定影响而迁移到局部极小值的问题。引入了迭代行为,以便每一代都可以自适应地选择其指导参数。使用一部分应用的数学优化测试函数(即Ackley,余弦混合物,Neumaier,Rosenbrock和Rastragin)来评估改进算法的性能。结果表明,改进的算法在5个测试函数中的四(4)个中表现更好。

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