| 引用本文: | 赵华敏,陈开周.全局优化的神经网络方法[J].控制理论与应用,2002,19(6):824~828.[点击复制] |
| ZHAO Hua-min,CHEN Kai-zhou.Neural network for global optimization[J].Control Theory and Technology,2002,19(6):824~828.[点击复制] |
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| 全局优化的神经网络方法 |
| Neural network for global optimization |
| 摘要点击 2969 全文点击 1701 投稿时间：2000-07-03 修订日期：2001-02-19 |
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| DOI编号 10.7641/j.issn.1000-8152.2002.6.002 |
| 2002,19(6):824-828 |
| 中文关键词 全局优化 神经网络 收敛性 下降点 |
| 英文关键词 global optimization neural network convergence descent point |
| 基金项目 |
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| 中文摘要 |
| 提出了一种解全局优化问题的神经网络模型, 并分析了该模型的收敛性与可行性. 然后, 给出了一个算法, 严格地证明了该算法对优化问题的任意给定的初始点, 都能收敛到它的一个全局极小点. 最后的仿真结果表明, 该算法是有效的. |
| 英文摘要 |
| A neural network model for solving global optimization problems is proposed. The convergence and feasibility of the model are analyzed. Then an algorithm is provided. It is strictly proved that for an arbitrarily given initial point of an optimization problem, the algorithm converges to a global minimizer of the problem. Finally, simulation results are presented to \{illustrate\} the effectiveness of the algorithm. |
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