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

Part of the Studies in Computational Intelligence book series (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.

Keywords

  • Sedimentation
  • Machine learning
  • Sensor networks
  • BPNN
  • RBFN

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Correspondence to Dillip K. Ghose .

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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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