Computational Intelligence Based Optimization Of Manufacturing Process For Sustainable Materials


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Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials


Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials

Author: Deepak Sinwar

language: en

Publisher: CRC Press

Release Date: 2023-09-25


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The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials


Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials

Author: Deepak Sinwar

language: en

Publisher: CRC Press

Release Date: 2023-09-25


DOWNLOAD





The text comprehensively discusses computational models including artificial neural networks, agent-based models, and decision field theory for reliability engineering. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, computer engineering, and materials science. Discusses the development of sustainable materials using metaheuristic approaches. Covers computational models such as agent-based models, ontology, and decision field theory for reliability engineering. Presents swarm intelligence methods such as ant colony optimization, particle swarm optimization, and grey wolf optimization for solving the manufacturing process. Include case studies for industrial optimizations. Explores the use of computational optimization for reliability and maintainability theory. The text covers swarm intelligence techniques including ant colony optimization, particle swarm optimization, cuckoo search, and genetic algorithms for solving complex industrial problems of the manufacturing industry as well as predicting reliability, maintainability, and availability of several industrial components.

Artificial Intelligence of Things (AIoT)


Artificial Intelligence of Things (AIoT)

Author: Fadi Al-Turjman

language: en

Publisher: Elsevier

Release Date: 2024-09-11


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Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings.The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency. - Provides readers with up-to-date and comprehensive information on the latest advancements in AIoT, including wireless technologies, pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power - Explores the possibilities of new domains, services, and business models that can be created using AIoT - Discusses the potential impact of AIoT on society, including its potential to improve efficiency, reduce costs, and enhance quality of life