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  • 标题:Study of Hybrid Neurofuzzy Inference System for Forecasting Flood Event Vulnerability in Indonesia
  • 本地全文:下载
  • 作者:Sri Supatmi ; Sri Supatmi ; Rongtao Hou
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2019
  • 卷号:2019
  • DOI:10.1155/2019/6203510
  • 出版社:Hindawi Publishing Corporation
  • 摘要:An experimental investigation was conducted to explore the fundamental difference among the Mamdani fuzzy inference system (FIS), Takagi–Sugeno FIS, and the proposed flood forecasting model, known as hybrid neurofuzzy inference system (HN-FIS). The study aims finding which approach gives the best performance for forecasting flood vulnerability. Due to the importance of forecasting flood event vulnerability, the Mamdani FIS, Sugeno FIS, and proposed models are compared using trapezoidal-type membership functions (MFs). The fuzzy inference systems and proposed model were used to predict the data time series from 2008 to 2012 for 31 subdistricts in Bandung, West Java Province, Indonesia. Our research results showed that the proposed model has a flood vulnerability forecasting accuracy of more than 96% with the lowest errors compared to the existing models.
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