Hybrid forecasting model-based data mining and genetic algorithm-adaptive particle swarm optimisation: a case study of wind speed time series

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	Hybrid forecasting model-based data mining and genetic algorithm-adaptive particle swarm optimisation: a case study of wind speed time series
	Wang, JZ; Zhang, FY; Liu, F; Ma, JJ
刊名	IET RENEWABLE POWER GENERATION
	2016-03
卷号	10 期号:3 页码:287-298
关键词	data mining genetic algorithms particle swarm optimisation wavelet neural nets power engineering computing wind power weather forecasting hybrid forecasting model-based data mining genetic algorithm-adaptive particle swarm optimisation algorithm wind speed time series wind energy renewable energy source wind speed forecasting wavelet neural network model WNN model wind farm eastern China paired-sample T test
ISSN号	1752-1416
通讯作者	Zhang, FY (reprint author), Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R China.
学科主题	Science & Technology - Other Topics; Energy & Fuels; Engineering
出版地	HERTFORD
语种	英语
WOS记录号	WOS:000371789100002
内容类型	期刊论文
源URL	[http://ir.lzu.edu.cn/handle/262010/180789]
专题	数学与统计学院_期刊论文
推荐引用方式 GB/T 7714	Wang, JZ,Zhang, FY,Liu, F,et al. Hybrid forecasting model-based data mining and genetic algorithm-adaptive particle swarm optimisation: a case study of wind speed time series[J]. IET RENEWABLE POWER GENERATION,2016,10(3):287-298.
APA	Wang, JZ,Zhang, FY,Liu, F,&Ma, JJ.(2016).Hybrid forecasting model-based data mining and genetic algorithm-adaptive particle swarm optimisation: a case study of wind speed time series.IET RENEWABLE POWER GENERATION,10(3),287-298.
MLA	Wang, JZ,et al."Hybrid forecasting model-based data mining and genetic algorithm-adaptive particle swarm optimisation: a case study of wind speed time series".IET RENEWABLE POWER GENERATION 10.3(2016):287-298.