Power Engineering and Intelligent Systems [electronic resource] : Proceedings of PEIS 2024, Volume 2 / edited by Vivek Shrivastava, Jagdish Chand Bansal, B. K. Panigrahi.

Colaborador(es): Shrivastava, Vivek [editor.] | Bansal, Jagdish Chand [editor.] | Panigrahi, B. K [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes in Electrical Engineering ; 1247Editor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XVI, 535 p. 275 illus., 243 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819767144Tema(s): Computational intelligence | Electric power production | Electric machinery | Artificial intelligence | Computational Intelligence | Electrical Power Engineering | Electrical Machines | Artificial IntelligenceFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer Nature eBookResumen: 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.
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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.

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.

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