基于GA-ANFIS-FCM算法的电力能源预测  

Power Energy Prediction Based on GA-ANFIS-FCM Algorithm

作　　者：陈亮[1] 朱元凯[1] 李长英[1] 谢清强 CHEN Liang;ZHU Yuan-kai;LI Chang-ying;XIE Qing-qiang(Taishan Vocational and Technical College,Taian 271000,Shandong)

机构地区：[1]泰山职业技术学院,山东泰安271000

出　　处：《电脑与电信》2023年第9期83-86,共4页Computer & Telecommunication

摘　　要：电力公司为居民和企业提供不间断的电力供应是其主要责任。预测电力能源需求总是保证电力供应的最佳方案。将遗传算法(GA)、聚类算法(FCM)和自适应神经模糊推理系统(ANFIS)相结合,构造了GA–ANFIS–FCM混合算法,并将算法用于电力能源预测。通过与独立的ANFIS–FCM模型比较,验证了GA–ANFIS–FCM3为最佳子模型。Electric power companies are primarily responsible for providing uninterrupted power supply to residents and businesses.Predicting electricity energy demand is always the best solution to ensure electricity supply.A GA-ANFIS-FCM hybrid algorithm is constructed by combining genetic algorithm(GA),clustering algorithm(FCM),and adaptive neural fuzzy inference system(ANFIS),and the algorithm is applied to power energy prediction.By comparing with the independent ANFIS-FCM model,it is verified that GA ANFIS FCM3 is the optimal submodel.

关 键 词：GA FCM ANFIS 电力能源预测 

分 类 号：TM715[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]