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Sedimentation Process and Its Assessment Through Integrated Sensor Networks and Machine Learning Process

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Computational Intelligence in Sensor Networks

Part of the book series: Studies in Computational Intelligence ((SCI,volume 776))

Abstract

Capacity of suspended sediment is an important phenomenon for soil conservation structure. Sediment concentration is measured using sensors in a river reach. Sediment transport is basically in two forms, bed load and suspended load. The amount of load carried in suspension by a river mainly depends on the volume and velocity of the stream. Actual sedimentation patterns and depths are extremely difficult to evaluate. The main contribution of the research is the development of flow and sedimentation prediction models for each month of monsoon period using artificial neural networks. The frame work is tested on the river Mahanadi.

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology, Silchar, Assam, India

    Dillip K. Ghose & Sandeep Samantaray

Authors
  1. Dillip K. Ghose
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  2. Sandeep Samantaray
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Corresponding author

Correspondence to Dillip K. Ghose .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Silicon Institute of Technology, Bhubaneswar, India

    Bijan Bihari Mishra

  2. Department of Information and Communication, Fakir Mohan University, Balasore, Odisha, India

    Satchidanand Dehuri

  3. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Department of Computer Science and Engineering, Silicon Institute of Technology, Bhubaneswar, India

    Ajit Kumar Nayak

  5. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Bhabani Shankar Prasad Mishra

  6. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Himansu Das

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Ghose, D.K., Samantaray, S. (2019). Sedimentation Process and Its Assessment Through Integrated Sensor Networks and Machine Learning Process. In: Mishra, B., Dehuri, S., Panigrahi, B., Nayak, A., Mishra, B., Das, H. (eds) Computational Intelligence in Sensor Networks. Studies in Computational Intelligence, vol 776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-57277-1_20

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