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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032781114 ISBN 13: 9781032781112
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Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032781114 ISBN 13: 9781032781112
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Hardcover. Condition: new. Hardcover. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book:Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computingPresents a comparative analysis of machine learning algorithms for power consumption predictionDiscusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environmentIllustrates a data-driven optimization concept for modeling environmental and economic sustainabilityExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsThe text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032781114 ISBN 13: 9781032781112
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Hardcover. Condition: new. Hardcover. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility.This book:Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computingPresents a comparative analysis of machine learning algorithms for power consumption predictionDiscusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environmentIllustrates a data-driven optimization concept for modeling environmental and economic sustainabilityExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsThe text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering. This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Language: English
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032621664 ISBN 13: 9781032621661
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Hardcover. Condition: new. Hardcover. This book comprehensively discusses natureinspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques. It further covers important topics such as the use of machine learning and the Internet of Things and multiobjective optimization under Fermatean hesitant fuzzy and uncertain environment.This book:Addresses solving practical problems such as supply chain management, smart manufacturing, and healthcare analytics using intelligent computing and discusses solving the fuzzy inference system in ant colony optimization for traveling salesman problemPresents an overview of artificial intelligence (AI) and explainable AI decisionmaking (XAIDM) and illustrates a datadriven optimization concept for modeling environmental and economic sustainabilityDiscusses machine learningbased multiobjective optimization technique for load balancing in integrated fogcloud environmentExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsDiscusses sustainable transit of hazardous waste, green fractional transportation system, perishable inventory, Mestimation of functional regression operator, and intuitionistic fuzzy sets applicationsThe text is primarily written for graduate students and academic researchers in diverse fields, including operations research, mathematics, statistics, computer science, information and communication technology, and industrial engineering. The book discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques and covers important topics such as the use of machine learning and the internet of things, multi-objective optimization under Hesitant Fermatean Fuzzy and Uncertain environment. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Buch. Condition: Neu. Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making | Artificial Intelligence Applications | Irfan Ali (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | CRC Press | EAN 9781032781112 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Language: English
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032621664 ISBN 13: 9781032621661
Seller: CitiRetail, Stevenage, United Kingdom
Hardcover. Condition: new. Hardcover. This book comprehensively discusses natureinspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques. It further covers important topics such as the use of machine learning and the Internet of Things and multiobjective optimization under Fermatean hesitant fuzzy and uncertain environment.This book:Addresses solving practical problems such as supply chain management, smart manufacturing, and healthcare analytics using intelligent computing and discusses solving the fuzzy inference system in ant colony optimization for traveling salesman problemPresents an overview of artificial intelligence (AI) and explainable AI decisionmaking (XAIDM) and illustrates a datadriven optimization concept for modeling environmental and economic sustainabilityDiscusses machine learningbased multiobjective optimization technique for load balancing in integrated fogcloud environmentExplains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goalsDiscusses sustainable transit of hazardous waste, green fractional transportation system, perishable inventory, Mestimation of functional regression operator, and intuitionistic fuzzy sets applicationsThe text is primarily written for graduate students and academic researchers in diverse fields, including operations research, mathematics, statistics, computer science, information and communication technology, and industrial engineering. The book discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques and covers important topics such as the use of machine learning and the internet of things, multi-objective optimization under Hesitant Fermatean Fuzzy and Uncertain environment. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.