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Raj Mohan Singh

Researcher at Motilal Nehru National Institute of Technology Allahabad

Publications -  73
Citations -  894

Raj Mohan Singh is an academic researcher from Motilal Nehru National Institute of Technology Allahabad. The author has contributed to research in topics: Hydraulic structure & Crop yield. The author has an hindex of 12, co-authored 70 publications receiving 749 citations. Previous affiliations of Raj Mohan Singh include Dr. B. R. Ambedkar National Institute of Technology Jalandhar & Indian Institute of Technology Kanpur.

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Identification of groundwater pollution sources using GA-based linked simulation optimization model

TL;DR: In this paper, a GA-based simulation optimization approach is used for optimal identification of unknown groundwater pollution sources, where a flow and transport simulation model is externally linked to the GA based optimization model to simulate the physical processes involved.
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Identification of Unknown Groundwater Pollution Sources Using Artificial Neural Networks

TL;DR: In this article, the authors exploit the universal function approximation capability of a feed forward multilayer artificial neural network (ANN) to identify the unknown pollution sources in aquifers.
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Optimal cropping pattern in a canal command area

TL;DR: In this paper, a linear programming model was formulated to suggest the optimal cropping pattern giving the maximum net return at different water availability levels, subject to the following constraints: total available water and land during different seasons, the minimum area under wheat and rice for local food requirements, farmers' socioeconomic conditions, and preference to grow a particular crop in a specific area.
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Artificial neural network modeling for identification of unknown pollution sources in groundwater with partially missing concentration observation data

TL;DR: In this paper, an artificial neural network (ANN) based methodology is developed to identify unknown groundwater pollution sources in terms of these source characteristics for such a missing data scenario, when concentration measurement data over an initial length of time is not available.
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Groundwater Pollution Source Identification and Simultaneous Parameter Estimation Using Pattern Matching by Artificial Neural Network

TL;DR: In this paper, a multilayer, feed-forward ANN was used to estimate temporally and spatially varying unknown pollution sources, as well as to provide a rst-order estimation of unknown hydrogeologic parameters.