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SEDIMENT PREDICTION USING ANN BASED MULTILAYER PERCEPTRON (MLP) METHOD FOR HOSHANGABAD, MADHYA PRADESH
ISSN: 2277 - 7601
Publisher: author
SEDIMENT PREDICTION USING ANN BASED MULTILAYER PERCEPTRON (MLP) METHOD FOR HOSHANGABAD, MADHYA PRADESH
Indexed in
Agriculture and Food Sciences
ARTICLE-FACTOR
1.3
Article Basics Score: 3
Article Transparency Score: 2
Article Operation Score: 2
Article Articles Score: 3
Article Accessibility Score: 3
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-0202
Publisher: Ka More
International Journal Address (IAA):
IAA.ZONE/2277386527601
eISSN
:
2277 - 7601
VALID
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Abstract
For river structures, a sediment prediction is required. The quantity of suspended sediments has been estimated using station observations and machine learning modelling approaches. The sediment concentration was measured during this research using hydrometeorlogical data such as river flow, sediment and precipitation observed between 2006 and 2015 at the Hoshangabad station in Madhya Pradesh. The multilayer perceptron (MLP) approach with various learning rules and activation functions has been used to estimate the sediment load. The correlation coefficient (r), mean square error (MSE), normalized mean square error (NMSE), efficiency (CE), and coefficient of determination (R2) were used to compare these models. When comparing the observation and model results, the MLP models provided consistent results in estimating the silt content of rivers. Even so, the overall performance of LinerAxon
