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An Integrated Intelligent Cooperative Model for Water-Related Risk Management and Resource Scheduling

  • Yong-Sheng Ding
  • Xiao Liang
  • Li-Jun Cheng
  • Wei Wang
  • Rong-Fang Li
Part of the Intelligent Systems Reference Library book series (ISRL, volume 33)

Abstract

Risk management for natural disasters that focuses on early warning, dynamic scheduling and aftermath evaluation, has been one of the key technologies in the field of disaster prevention and mitigation. Some water-related disasters have common characteristics, which are usually generalized and then applied for establishing an integrated model to cope with these disasters. The rapid development of the artificial intelligence (AI) technique makes it possible to enhance the model with intelligent and cooperative features. Such type of model is firstly proposed in this chapter and then derived into two instances, which aim to solve problems in drought evaluation and water scheduling of reservoirs, respectively. The former is based on the radial base function neural network (RBFNN) and the later takes an improved particle swarm optimization (I-PSO) algorithm as its carrier for implementation. Simulation results demonstrate that the first model can make full use of the spatial and time data of the drought and high accuracy of evaluation and classification of the drought severity can therefore be acquired. The second model can distribute the water storage among the reservoirs timely and efficiently, which is of great significance of eliminating the damage of the seasonal droughts and floods occurred in the tributary.

Keywords

integrated intelligent model water disaster risk management water resource scheduling neural network particle swarm optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yong-Sheng Ding
    • 1
    • 2
  • Xiao Liang
    • 1
  • Li-Jun Cheng
    • 1
  • Wei Wang
    • 1
  • Rong-Fang Li
    • 1
    • 3
  1. 1.College of Information Sciences and TechnologyDonghua UniversityShanghaiP.R. China
  2. 2.Engineering Research Center of Digitized Textile & Fashion Technology, Ministry of EducationDonghua UniversityShanghaiP.R. China
  3. 3.Jiangxi Provincial Institute of Water SciencesNanchangP.R. China

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