文章基本信息

标题：DAILY STREAMFLOW PREDICTION ON TIME SERIES FORECASTING
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作者：AHMAD FIRDAUS KHAIR ; MOHD KHALID AWANG ; ZAHRATUL AMANI ZAKARAIA 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：4
出版社：Journal of Theoretical and Applied
摘要：Time series forecasting is a process that used present or past data to develop models for future prediction or trends. Stream flow prediction is considered as a challenging research activity because of its irregularity and unpredictable behavior. Researches have put their efforts and strategies in upgrading and improving the accuracy of streamflow analysis prediction. In this paper, time series forecasting using WEKA is used, analyzed and compared based on the following three algorithms, which are SMO Regression, Linear Regression and Multilayer Perception. The result shows that the SMO Regression algorithm provides better ability to predict more accurately compared to other algorithms.
关键词：Streamflow forecasting; SMO Regression; Linear Regression and Multilayer Perception