Optimization using Genetic Algorithms 基于遗传算法的最优化
This paper proposes a design of the self adaptive learning fuzzy controller based on Genetic Algorithms optimization.
本文提出一种基于基因算法优化的自学习模糊控制器的设计。
Applying genetic algorithms optimization principle to the Bowromi formula to determine proper a, B value. The result shows that GA is good for optimization and overall search.
将遗传算法的优化原理应用到鲍罗米公式中，用以确定合适的A、B值。其结果表明，遗传算法具有优良的全局搜索优化能力。
Through a hybrid way to combine Genetic Algorithms (GA) with convention nonlinear optimization, a study of automated match typical curve of well test has been done by this paper.
采用遗传算法与常规非线性优化方法相结合的途径，进行试并典型曲线的自动拟合研究。
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