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Research on Wind Power Prediction Modeling Based on Adaptive Feature Entropy Fuzzy Clustering
  • ISSN号:1673-3800
  • 期刊名称:《电气技术》
  • 时间:0
  • 分类:TP206.1[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构:[1]Shenyang Ligong University, Shenyang 110159, China, [2]Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110159, China
  • 相关基金:This work was supported by the Natural Science Foundation of China under contact(61233007 )
中文摘要:

Wind farm power prediction is proposed based on adaptive feature weight entropy fuzzy clustering algorithm.According to the fuzzy clustering method,a large number of historical data of a wind farm in Inner Mongolia are analyzed and classified.Model of adaptive entropy weight for clustering is built.Wind power prediction model based on adaptive entropy fuzzy clustering feature weights is built.Simulation results show that the proposed method could distinguish the abnormal data and forecast more accurately and compute fastly.

英文摘要:

Wind farm power prediction is proposed based on adaptive feature weight entropy fuzzy clustering algorithm. According to the fuzzy clustering method, a large number of historical data of a wind farm in Inner Mongolia are analyzed and classified. Model of adaptive entropy weight for clustering is built. Wind power prediction model based on adaptive entropy fuzzy clustering feature weights is built. Simulation results show that the proposed method could distinguish the abnormal data and forecast more accurately and compute fastly.

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期刊信息
  • 《电气技术》
  • 主管单位:中国科学技术协会
  • 主办单位:中国电工技术学会
  • 主编:赵争鸣
  • 地址:北京西城区三里河路46号
  • 邮编:100823
  • 邮箱:dianqijishu@126.com
  • 电话:010-68595026
  • 国际标准刊号:ISSN:1673-3800
  • 国内统一刊号:ISSN:11-5255/TM
  • 邮发代号:
  • 获奖情况:
  • 国内外数据库收录:
  • 被引量:4824