Proceedings of PEIS 2024, Volume 2 Shrivastava, Vivek. editor. edt http://id.loc.gov/vocabulary/relators/edt Bansal, Jagdish Chand. editor. edt http://id.loc.gov/vocabulary/relators/edt Panigrahi, B. K. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) text si 2024 1st ed. 2024. monographic eng

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access XVI, 535 p. 275 illus., 243 illus. in color. online resource. This book presents a collection of the high-quality research articles in the field of power engineering, grid integration, energy management, soft computing, artificial intelligence, signal and image processing, data science techniques, and their real-world applications. The papers are presented at International Conference on Power Engineering and Intelligent Systems (PEIS 2024), held during March 16–17, 2024, at National Institute of Technology Srinagar, Uttarakhand, India. Chapter 1: Study of the Optimal Sizing of Battery Energy Storage Systems for Microgrid Applications -- Chapter 2: Integrated State of Charge and State of Health Method for Operating Range Prediction in Electric Vehicles -- Chapter 3: Crime Prediction Using Ensemble Machine Learning Approach -- Chapter 4: Gated Recurrent Unit with Attention mechanism for IC50 Prediction model using Amyotrophic Lateral Sclerosis Related Proteins -- Chapter 5: Exploring Echo State Network for Detection of Gait Freezing in Parkinson's Patients Optimized through Modified Metaheuristics -- Chapter 6: Computer Vision-Based Self-Inflicted Violence Detection in High-Rise Environments using Deep Learning -- Chapter 7: Two Sliding Mode Control Strategies for Maglev Systems with Help of Kalman Filter -- Chapter 8: A Deep Learning Framework on Embedded ADAS Platform for Lane and Road Detection -- Chapter 9: Innovative Convolutional Neural Network Approach to Enhance Real-Time Face Recognition Accuracy -- Chapter 10: Tomato Plant Leaf Disease Prediction and Suggestion Using Deep Learning. etc. edited by Vivek Shrivastava, Jagdish Chand Bansal, B. K. Panigrahi. Computational intelligence Electric power production Electric machinery Artificial intelligence Computational Intelligence Electrical Power Engineering Electrical Machines Artificial Intelligence Q342 9789819767144 https://doi.org/10.1007/978-981-97-6714-4 https://doi.org/10.1007/978-981-97-6714-4 241204 20251030114604.0 978-981-97-6714-4