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Artificial Intelligence for Renewable Energy Systems
book

Artificial Intelligence for Renewable Energy Systems

by Ajay Kumar Vyas, S. Balamurugan, Kamal Kant Hiran, Harsh S. Dhiman
March 2022
Intermediate to advanced content levelIntermediate to advanced
272 pages
6h 54m
English
Wiley-Scrivener
Content preview from Artificial Intelligence for Renewable Energy Systems

2Artificial Intelligence as a Tool for Conservation and Efficient Utilization of Renewable Resource

Vinay N.1, Ajay Sudhir Bale1*, Subhashish Tiwari2 and Baby Chithra R.3

1Dept. of ECE, School of Engineering and Technology, CMR University, Bengaluru, India

2Dept. of ECE, Vignan's Foundation for Science, Technology & Research (Deemed to be University), Guntur, India

3Dept. of ECE, New Horizon College of Engineering, Bengaluru, India

Abstract

Energy is the most significant factor in the development of a society and country. As a basic requirement, it is important to provide safe, inexpensive, uninterrupted, secure, and diversified energy supplies. At present, the major source of energy is produced from renewable and fossil resources. As the level of fossil resources is decreasing day by day, the application of renewable resources is increasing. This work describes the efficient utilization of renewable resources like water, solar, wind, and geothermal using various Artificial Intelligence (AI) techniques. The models like Back-Propagation, Multilayer Perceptron (MLP), Whale Optimization Algorithm (WOA), Radial Basis Function Neural Network (RBFN), Bayesian Regularization (BR), Levenberg-Marquardt (LM) algorithm, and Gradient Descent with momentum and adaptation learning rate back-propagation algorithm (GDX) are used in the forecasting of water resources. For solar energy, models such as MLP, Fuzzy ART (Adaptive Resonance Theory), RB, and Shark Smell Optimization (SSO) algorithm ...

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Publisher Resources

ISBN: 9781119761693Purchase Link