| 基于人工智能方法的无源光网络优化规划 |
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| 引用本文： | 陈亚华,刘锦高,赵文武,卞玉存.基于人工智能方法的无源光网络优化规划[J].光通信研究,2001(3):35-38. |
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| 作者姓名： | 陈亚华 刘锦高 赵文武 卞玉存 |
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| 作者单位： | 1. 上海电信技术研究所,
2. 华东师范大学 电子科学技术系, |
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| 摘 要： | 使用人工智能方法对PON网络拓扑结构进行优化，以富士通FPX－1000无源光网络系统为例进行了仿真实验，并对遗传算法，增添算法和Hopfield网络方法进行比较，仿真结果表明遗传算法明显优于增添算法和Hopfield网络方法，遗传算法可使网络建设代价最小化，它非常好地解决了PON规划问题。
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| 关 键 词： | 无源光网络 遗传算法 Hopfield网络 人工智能 网络规划 |
| 文章编号： | 1005-8788(2001)03-0035-04 |
| 修稿时间： | 2000年7月11日 |
Passive optical networks optimization planning based on artificial intelligence methods |
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| CHEN Ya-hua,LIU Jin-gao,ZHAO Wen-wu,BIAN Yu-cun.Passive optical networks optimization planning based on artificial intelligence methods[J].Study on Optical Communications,2001(3):35-38. |
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| Authors: | CHEN Ya-hua LIU Jin-gao ZHAO Wen-wu BIAN Yu-cun |
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| Abstract: | This paper uses artificial intelligence methods to optimize the PON topology. The simulation experiments of PON systems such as FPX 1000 are carried out. The genetic algorithm (GA),add algorithm (AA) and Hopfield net approach (HNA) are compared,The simulation results show that GA is better than AA and HNA. GA can minimize installation cost of PON and realize the optimization of the passive optical networks with satisfaction. |
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| Keywords: | passive optical network genetic algorithm add algorithm Hopfield net approach network planning |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
