An Extreme Learning Machine and Gene Expression Programming-Based Hybrid Model for Daily Precipitation Prediction

Accurate daily precipitation prediction is crucially important. However, it is difficult to predict the precipitation accurately due to inherently complex meteorological factors and dynamic behavior of weather. Recently, considerable attention has been devoted in soft computing-based prediction appr...

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Veröffentlicht in:	International journal of computational intelligence systems Jg. 12; H. 2; S. 1512 - 1525
Hauptverfasser:	Peng, Yuzhong, Zhao, Huasheng, Zhang, Hao, Li, Wenwei, Qin, Xiao, Liao, Jianping, Liu, Zhiping, Li, Jie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.01.2019 Springer Nature B.V Springer
Schlagworte:	Artificial neural networks Errors Extreme Learning Machine Gene expression Gene Expression Programming Machine learning Modelling Precipitation Quantitative precipitation prediction Rainfall Rainfall prediction Regional development Research Article Soft computing Weather Gene Expression Programming Extreme Learning Machine Soft computing Quantitative precipitation prediction Rainfall prediction
ISSN:	1875-6891, 1875-6883, 1875-6883
Online-Zugang:	Volltext
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