Lokasi: Radial Basis Function (RBF) Neural Network: Effect of Hidden Neuron Number, Training Data Size, and Input Variables on Rainfall Intensity Forecasting

Main Authors:	Chai, Soo See; Department of Software Engineering and Computing, Faculty of Computer Science and Information Technology, University Malaysia Sarawak (UNIMAS), Malaysia, Wong, Wei Keat; Department of Software Engineering and Computing, Faculty of Computer Science and Information Technology, University Malaysia Sarawak (UNIMAS), Malaysia, Goh, Kok Luong; School of Innovative Technology, International College of Advanced Technology Sarawak (i-CATS), Malaysia, Wang, Hui Hui; Department of Software Engineering and Computing, Faculty of Computer Science and Information Technology, University Malaysia Sarawak (UNIMAS), Malaysia, Wang, Yin Chai; Department of Software Engineering and Computing, Faculty of Computer Science and Information Technology, University Malaysia Sarawak (UNIMAS), Malaysia
Other Authors:	Department of Irrigation and Drainage (DID) Kuching, Sarawak, UNIMAS Special FRGS 2016 Cycle with project no: F08/SpFRGS/1528/2017
Format:	Article info application/pdf eJournal
Bahasa:	eng
Terbitan:	International Journal on Advanced Science, Engineering and Information Technology , 2019
Subjects:	rainfall radial basis function intensity forecasting meteorology data
Online Access:	http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/10239 http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/10239/pdf_1256

Koleksi	International Journal on Advanced Science, Engineering and Information Technology
Gedung	Indonesian Society for Knowledge and Human Development
Institusi	Indonesian Society for Knowledge and Human Development
Kota	-
Provinsi	DKI JAKARTA
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