Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.
Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant installation site is an issue of relevance. Environmental impact assessment is often used as a legislative requirement in site selection for decades. The purpose of this current work is to develop a model for decision makers to rank or classify various power plant projects according to multiple criteria attributes such as air quality, water quality, cost of energy delivery, ecological impact, natural hazard, and project duration. The case study in the paper relates to the application of multilayer perceptron trained by genetic algorithm for ranking various power plant locations in India.
Department of Electrical Engineering, National Institute of Technology Manipur, Manipur, India.
Benjamin A
0000-0002-4608-1462
BA
Shimray
Department of Computer Science & Engineering, National Institute of Technology Manipur, Manipur, India.
Kh Manglem
KM
Singh
Department of Computer Science & Engineering, National Institute of Technology Manipur, Manipur, India.
Thongam
T
Khelchandra
Department of Electrical Engineering, NERIST, Nirjuli, India.
R K
RK
Mehta
D000465:Algorithms; D004777:Environment; D006801:Humans; D007194:India; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D011210:Power Plants