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基于ANFIS的长期电力负荷预测模型

Long-Term Load Forecasting Model Based on ANFIS

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【作者】 王军吕元锋陈俊曹菁菁

【Author】 WANG Jun1, Lü Yuan-feng1, CHEN Jun1, CAO Jing-jing2 (1. Dept. of Electrical Engineering, Anhui University of Technology & Science, Wuhu 241000, China; 2. School of Mechanics & Dynamics Engineering, Shanghai JiaoTong University, Shanghai 200030, China)

【机构】 安徽工程科技学院电气工程系上海交通大学机械与动力工程学院 安徽芜湖241000安徽芜湖241000上海200030

【摘要】 某电力公司的长期负荷预测模型,利用自适应神经网络模糊推理系统(ANFIS)建立。其结构分为计算输入的模糊隶属度、每条规则适用度、适用度归一化、每条规则输出及模糊系统输出5层。系统网络中含14个待定的前件和后件参数。采用Matlab编程,通过Sugeno和evalfis函数训练ANFIS,按指定指标得到这些参数,实现模糊预测。

【Abstract】 The ANFIS was adopted by the long-term load forecasting model to establish power company. Its structure was divided into calculating input fuzzy membership degree layer, every rule application degree layer, normalization of application degree layer, every rule output layer and fuzzy system output layer. There are 14 undetermined parameters named predictor and consequent. The Matlab programmer was adopted to train ANFIS through Sugeno and evalfis function; then, those parameters were achieved according to appointed indexes and fuzzy forecasting were realized.

  • 【文献出处】 兵工自动化 ,Ordnance Industry Automation , 编辑部邮箱 ,2006年07期
  • 【分类号】TM715
  • 【下载频次】131
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