| 引用本文: | 王志征,余岳峰,姚国平.基于主成分分析法和自适应神经模糊推理系统的电力负荷预测[J].电力自动化设备,2003,(9):39-41 |
| .Power load forecast based on principal component analysis and adaptive neuro-fuzzy inference system[J].Electric Power Automation Equipment,2003,(9):39-41 |
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| 摘要: |
| 提出了一种基于主成分分析法与自适应神经模糊推理相结合的电力系统负荷预测方法，通过对影响电力负荷的相关因素进行主成分分析，减少自适应神经模糊推理系统的输入量，可以提高系统预测的效率。算例表明所提出方法是有效的和可行的。 |
| 关键词: 主成分分析 自适应神经模糊推理系统 负荷预测 |
| DOI： |
| 分类号:TM715 |
| 基金项目: |
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| Power load forecast based on principal component analysis and adaptive neuro-fuzzy inference system |
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WANG Zhi-zheng YU Yue-feng YAO Guo-ping
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| Abstract: |
| Based on the principal component analysis and adaptive neuro-fuzzy inference system,a power load forecast method is put forward.Applying principal component analysis to the relevant factors that affect power load reduces the input variables and simplifies the structure of adaptive neuro-fuzzy inference system,which improves forecast efficiency.Calculation example shows that the method is feasible and effective. |
| Key words: principal component analysis,adaptive neuro-fuzzy inference system,load forecast%, |
