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Frontiers in Nature-Inspired Industrial Optimization

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Frontiers in Nature-Inspired Industrial Optimization/ edited by Mahdi Khosravy, Neeraj Gupta, Nilesh Patel.
other author:	Khosravy, Mahdi.
Description:	XII, 235 p. 94 illus., 76 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-981-16-3128-3
ISBN:	9789811631283

Frontiers in Nature-Inspired Industrial Optimization
Frontiers in Nature-Inspired Industrial Optimization[electronic resource] /edited by Mahdi Khosravy, Neeraj Gupta, Nilesh Patel. - 1st ed. 2022. - XII, 235 p. 94 illus., 76 illus. in color.online resource. - Springer Tracts in Nature-Inspired Computing,2524-5538. - Springer Tracts in Nature-Inspired Computing,.

Association Rules Over Time -- A Study of Crossover Operators in Genetic Algorithms -- Memetic Strategies for Network Design Problems -- A Coronavirus Optimization Algorithm for Solving The Container Retrieval Problem -- Optimum Outlier Detection in Internet of Things Industries Using Autoencoder -- Particle Swarm Optimization Advances in Internet of Things Industry -- Reconfiguration of Electric Power Distribution Networks: A Typical Application of Metaheuristics in Electrical Power Field -- Reconfiguration of Electric Power Distribution Networks: A Typical Application of Metaheuristics in Electrical Power Field -- Multi Objective Optimization and Decision Making for Net Zero Energy Smart House -- Using Fuzzy Approach In Determining Critical Parameters for Optimum Safety Functions In Mega Projects (Case Study: Iran's Construction Industry) -- Using Fuzzy Approach in Determining Critical Parameters for Optimum Safety Functions in Mega Projects (Case Study: Iran's Construction Industry) -- Evolutionary Machine Learning Powered by Genetics Algorithm for Iot-Specific Health Monitoring of Agriculture Vehicles.

The book provides a collection of recent applications of nature inspired optimization in industrial fields. Different optimization techniques have been deployed, and different problems have been effectively analyzed. The valuable contributions from researchers focus on three ultimate goals (i) improving the accuracy of these techniques, (ii) achieving higher speed and lower computational complexity, and (iii) working on their proposed applications. The book is helpful for active researchers and practitioners in the field. .

ISBN: 9789811631283

Standard No.: 10.1007/978-981-16-3128-3doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Frontiers in Nature-Inspired Industrial Optimization
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