| 基于可加性模糊系统的负荷时间序列预测 |
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| 引用本文： | 刘耀年,曾令全,张文生,李玉玲.基于可加性模糊系统的负荷时间序列预测[J].电工电能新技术,2002,21(4):23-25,73. |
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| 作者姓名： | 刘耀年 曾令全 张文生 李玉玲 |
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| 作者单位： | 东北电力学院,吉林,吉林,132012 |
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| 摘 要： | 本文依据可加性模糊系统理论，提出了一种新的预测方法，利用聚类方法与有监督学习相结合的训练方法，提高了系统的函数逼近能力。仿真结果表明，系统学习速度快、预测精度高，在电力负荷时间序列预测中获得相当满意的结果。
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| 关 键 词： | 可加性模糊系统 负荷时间序列预测 电力系统 聚类学习算法 有监督学习 |
| 文章编号： | 1003-3076(2002)04-0023-03 |
Load time series forecasting based on additive fuzzy systems |
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| LIU Yao\|nian,ZENG Ling\|quan,ZHANG Wen\|sheng,LI Yu\|ling.Load time series forecasting based on additive fuzzy systems[J].Advanced Technology of Electrical Engineering and Energy,2002,21(4):23-25,73. |
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| Authors: | LIU Yao\|nian ZENG Ling\|quan ZHANG Wen\|sheng LI Yu\|ling |
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| Abstract: | In this paper, we show that additive fuzzy system can be used in the prediction of short\|term load time series. By using optimal cluster algorithm in combination with supervised learning of training system, functional approximation efficiency is improved. Simulations results show that the learning algorithm has the features of quick convergence and high forecasting precision. Fairly satisfactory results can be acquired for power load time series forecasting. |
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| Keywords: | additive fuzzy system cluster learning algorithm supervised learning load time series prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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