04331nam a22006135i 4500 978-981-97-5718-3 DE-He213 20251030113258.0 cr nn 008mamaa 241103s2024 si | s |||| 0|eng d 9789819757183 978-981-97-5718-3 10.1007/978-981-97-5718-3 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Intelligent Methods in Electrical Power Systems [electronic resource] / edited by Chetan B. Khadse, Ishaan R. Kale, Apoorva S. Shastri. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XIII, 171 p. 100 illus., 79 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Engineering Optimization: Methods and Applications, 2731-4057 Review on intelligent methods in Electrical power systems -- Investigation of Electric Load Forecasting Methods: A Weka Application (Regression and Optimization) -- Integration of Intelligent Systems for Efficient Smart Grid Management -- An Application of Artificial Bee Colony and Cohort Intelligence in Automatic Generation Control of Thermal Power System -- Distribution System Losses and Its Allocation: Effects of Load Power Factor and Distributed Generations -- IoT based Intelligent Home Automation System using IFTTT with Google Assistant -- A review on Meta-heuristic Optimization Methods for Efficient Power System Operation -- Ice thickness control circuit to automate the milk chilling system -- SCGB Neural Network based Micro-grid AC Side Fault Analysis -- Artificial intelligence based system for detection and classification of faults in Induction motor. This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering. It covers various power system applications including efficient power system operation, load forecasting, fault analysis, home automation and efficient smart grid management. Each application is accompanied by case studies and a literature review in self-contained chapters. The book is dedicated to study the effectiveness of intelligent methods in addressing the power system problems and its mitigation using optimization algorithms. It discusses several optimization algorithms such as random forest algorithm, metaheuristic algorithm, scaled conjugate gradient descent algorithm, artificial bee colony algorithm etc. and their usability in intelligent decision makers for the various optimization problems in electrical engineering. This timely book serves as a practical guide and reference sources for students, researchers and professionals. Computational intelligence. 64052 Electric power production. 65675 Artificial intelligence. 58441 Algorithms. 58677 Mathematical optimization. 65522 Computational Intelligence. 64052 Electrical Power Engineering. 65867 Artificial Intelligence. 58441 Algorithms. 58677 Optimization. 65528 Khadse, Chetan B. editor. edt http://id.loc.gov/vocabulary/relators/edt 87006 Kale, Ishaan R. editor. edt http://id.loc.gov/vocabulary/relators/edt 87007 Shastri, Apoorva S. editor. edt http://id.loc.gov/vocabulary/relators/edt 87008 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819757176 Printed edition: 9789819757190 Printed edition: 9789819757206 Engineering Optimization: Methods and Applications, 2731-4057 87009 https://doi.org/10.1007/978-981-97-5718-3 ZDB-2-INR ZDB-2-SXIT 64706 64706