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Intelligent Methods in Electrical Power Systems [electronic resource] / edited by Chetan B. Khadse, Ishaan R. Kale, Apoorva S. Shastri.

Contributor(s): Material type: TextSeries: Engineering Optimization: Methods and ApplicationsPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XIII, 171 p. 100 illus., 79 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789819757183
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • Q342
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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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.

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