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Drought Prediction and River Network Optimization in Maharashtra Region

  • Sakshi SubediEmail author
  • Krutika Pasalkar
  • Girisha Navani
  • Saili Kadam
  • Priya Raghavan Nair Lalitha
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1046)

Abstract

Drought affects the natural environment of an area when it persists for a longer period, prompting dry season. Thus, such dry season can have many annihilating effects on river networks. The paper address this predominant issue in the form of an alternate solution which re-routes the course of the natural water sources, like rivers, through those areas, where the water supply is minimal in comparison with the demand, in a cost-effective and highly beneficial manner. In the proposed model, Deep Belief Network (DBN) is utilized to foresee the early event of drought in Marathwada region of Maharashtra. Standard Precipitation Index is used to categorize the severity of drought. Using DBN model, the accuracy obtained with root mean square error of 0.04469, mean absolute error of 0.00207 is far better over the traditional methods. The application of Swarm optimization technique is used to address the problem of drought mitigation through providing a re-routed path.

Keywords

Deep Belief Network Drought prediction Multi-Swarm Optimization technique River network optimization Standard Precipitation Index (SPI) 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Sakshi Subedi
    • 1
    • 2
    Email author
  • Krutika Pasalkar
    • 1
    • 2
  • Girisha Navani
    • 1
    • 2
  • Saili Kadam
    • 1
    • 2
  • Priya Raghavan Nair Lalitha
    • 1
    • 2
  1. 1.Department of Computer EngineeringUniversity of Mumbai, Vivekanand Education Society’s Institute of TechnologyMumbaiIndia
  2. 2.Computer Engineering DepartmentVivekanand Education Society’s Institute of TechnologyMumbaiIndia

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