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提出了求解不等式约束非线性优化问题的群体复合形进化算法 ,提出的算法能充分利用目标函数值的信息、优化搜索过程具有较强的方向性和目标性 ,收敛速度较快 ,且是全局优化算法 ;将群体复合形进化算法应用于三层前向人工神经网络逼近 ,提出了三层前向人工神经网络全局最优逼近算法 ;将三层前向人工神经网络全局最优逼近算法应用于实例 ,表明了提出的全局最优逼近算法的有效性 .
A group complex evolutionary algorithm is proposed to solve the nonlinear optimization problem with inequality constraints. The proposed algorithm can make full use of the information of the objective function value. The optimal search process has strong directionality and goal, converges quickly and is globally optimized Algorithm; the complex compound evolutionary algorithm is applied to the three-layer forward artificial neural network approximation, and the global optimal approximation algorithm of the three-layer forward artificial neural network is proposed; the global optimal approximation algorithm of the three-layer forward artificial neural network is applied to the instance , Shows the effectiveness of the proposed global optimal approximation algorithm.