| 人工神经元网络负荷静态特性辨识的并行算法 |
| |
| 引用本文： | 韩晓言 韩祯祥. 人工神经元网络负荷静态特性辨识的并行算法[J]. 电力系统自动化, 1994, 18(11): 21-26 |
| |
| 作者姓名： | 韩晓言 韩祯祥 |
| |
| 作者单位： | (浙江大学，杭州) |
| |
| 摘 要： | 基于人工神经元网络理论，对概率学习算法(Probabilistic Learni ng)和误差反向传播算法(简称BP算法)的电力系统负荷静态特性辨识的并行算法进行 了研究，并对这两种算法的计算复杂性和通信复杂性以及并行效率进行了分析。结果表明， 这两种算法都有较好的并行性能。
|
| 关 键 词： | 并行算法 电力负荷 辨识 人工神经元网络 |
| 收稿时间： | 1900-01-01 |
| 修稿时间： | 1900-01-01 |
THE PARALLEL ALGORITHM OF THE STATIC CHARACTERISTIC IDENTIFICATION OF ELECTRIC LOADS VIA ARTIFICATION NEURAL NETWORKS |
| |
| Han Xiaoyan,Han Zhenxiang. THE PARALLEL ALGORITHM OF THE STATIC CHARACTERISTIC IDENTIFICATION OF ELECTRIC LOADS VIA ARTIFICATION NEURAL NETWORKS[J]. Automation of Electric Power Systems, 1994, 18(11): 21-26 |
| |
| Authors: | Han Xiaoyan Han Zhenxiang |
| |
| Abstract: | In this paper ,the parallel algorithm of the static characteristic identification of electric loads based on Artificial Neural Networks(ANN)is developed by applying Probabilistic Learning and Error Back Propagation ( BP Algorithm). The computation complexity,communication complexity and the parallel effi-ciency of these two methods are given. The results show that both of these two parallel algorithms have good performance. |
| |
| Keywords: | parallel algorithm electric loads identification artificial neural networks |
| 本文献已被 CNKI 维普 等数据库收录！ |
| 点击此处可从《电力系统自动化》浏览原始摘要信息 |
|
点击此处可从《电力系统自动化》下载免费的PDF全文 |
