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  • 标题:Trend analysis and artificial neural networks forecasting for rainfall prediction
  • 本地全文:下载
  • 作者:Oseni Taiwo Amoo, Bloodless Dzwairo, 2016. Oseni Taiwo Amoo ; Oseni Taiwo Amoo, Bloodless Dzwairo, 2016. Oseni Taiwo Amoo ; Department of Civi
  • 期刊名称:Environmental Economics
  • 印刷版ISSN:1998-6041
  • 电子版ISSN:1998-605X
  • 出版年度:2016
  • 卷号:7
  • 期号:4
  • 页码:149-160
  • DOI:10.21511/ee.07(4-1).2016.07
  • 语种:English
  • 出版社:LLC "CPC "Business Perspectives"
  • 摘要:The growing severe damage and sustained nature of the recent drought in some parts of the globe have resulted in the need to conduct studies relating to rainfall forecasting and effective integrated water resources management. This research examines and analyzes the use and ability of artificial neural networks (ANNs) in forecasting future trends of rainfall indices for Mkomazi Basin, South Africa. The approach used the theory of back propagation neural networks, after which a model was developed to predict the future rainfall occurrence using an environmental fed variable for closing up. Once this was accomplished, the ANNs’ accuracy was compared against a traditional forecasting method called multiple linear regression. The probability of an accurate forecast was calculated using conditional probabilities for the two models. Given the accuracy of the forecast, the benefits of the ANNs as a vital tool for decision makers in mitigating drought related concerns was enunciated.
  • 关键词:artificial neural networks; drought; rainfall case forecast; multiple linear regression
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