| Titre : |
Artificial intelligence in industry 4.0 and 5G technology |
| Type de document : |
texte imprimé |
| Auteurs : |
Pandian Vasant, Éditeur scientifique ; Elias Munapo, Éditeur scientifique ; J. Joshua Thomas (1973-....), Éditeur scientifique ; Gerhard-Wilhelm Weber, Éditeur scientifique |
| Editeur : |
Hoboken, NJ : John Wiley et Sons, Inc. |
| Année de publication : |
2022 |
| Importance : |
XXX, 321 p. |
| Présentation : |
ill. |
| Format : |
24 cm |
| ISBN/ISSN/EAN : |
978-1-119-79876-7 |
| Note générale : |
Ref. Bibliogr. en fin de chapitres. - Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Artificial intelligence -- Industrial applications
Industry 4.0
5G mobile communication systems
Intelligence artificielle -- Applications industrielles
Industrie
Communications mobiles 5G |
| Index. décimale : |
004.896 Intelligence artificielle dans les systèmes industriels |
| Résumé : |
Artificial Intelligence in Industry 4.0 and 5G Technology Explores innovative and value-added solutions for application problems in the commercial, business, and industry sectors As the pace of Artificial Intelligence (AI) technology innovation continues to accelerate, identifying the appropriate AI capabilities to embed in key decision processes has never been more critical to establishing competitive advantage. New and emerging analytics tools and technologies can be configured to optimize business value, change how an organization gains insights, and significantly improve the decision-making process across the enterprise. Artificial Intelligence in Industry 4.0 and 5G Technology helps readers solve real-world technological engineering optimization problems using evolutionary and swarm intelligence, mathematical programming, multi-objective optimization, and other cutting-edge intelligent optimization methods. Contributions from leading experts in the field present original research on both the theoretical and practical aspects of implementing new AI techniques in a variety of sectors, including Big Data analytics, smart manufacturing, renewable energy, smart cities, robotics, and the Internet of Things (IoT). Presents detailed information on meta-heuristic applications with a focus on technology and engineering sectors such as smart manufacturing, smart production, innovative cities, and 5G networks. Offers insights into the use of metaheuristic strategies to solve optimization problems in business, economics, finance, and industry where uncertainty is a factor. Provides guidance on implementing metaheuristics in different applications and hybrid technological systems. Describes various AI approaches utilizing hybrid meta-heuristics optimization algorithms, including meta-search engines for innovative research and hyper-heuristics algorithms for performance measurement. Artificial Intelligence in Industry 4.0 and 5G Technology is a valuable resource for IT specialists, industry professionals, managers and executives, researchers, scientists, engineers, and advanced students an up-to-date reference to innovative computing, uncertainty management, and optimization approaches. |
| Note de contenu : |
Summary :
1. Dynamic Key-based Biometric End-User Authentication Proposal for IoT in Industry
2. Decision Support Methodology for Scheduling Orders in Additive Manufacturing
3. Significance of Consuming 5G-Built Artificial Intelligence in Smart Cities
4. Neural Network Approach to Segmentation of Economic Infrastructure Objects on High-Resolution Satellite Images
5. The Impact of Data Security on the Internet of Things
6. Sustainable Renewable Energy and Waste Management on Weathering Corporate Pollution
7. Adam Adaptive Optimization Method for Neural Network Models Regression in Image Recognition Tasks
8. Application of Integer Programming in Allocating Energy Resources in Rural Africa
9. Feasibility of Drones as the Next Step in Innovative Solution for Emerging Society
10. Designing a Distribution Network for a Soda Company: Formulation and Efficient Solution Procedure
11. Machine Learning and MCDM Approach to Characterize Student Attrition in Higher Education
12. A Concise Review on Recent Optimization and Deep Learning Applications in Blockchain Technology
13. Inventory Routing Problem with Fuzzy Demand and Deliveries with Priority
14. Comparison of Defuzzification Methods for Project Selection
15. Re-Identification-Based Models for Multiple Object Tracking |
Artificial intelligence in industry 4.0 and 5G technology [texte imprimé] / Pandian Vasant, Éditeur scientifique ; Elias Munapo, Éditeur scientifique ; J. Joshua Thomas (1973-....), Éditeur scientifique ; Gerhard-Wilhelm Weber, Éditeur scientifique . - Hoboken, NJ : John Wiley et Sons, Inc., 2022 . - XXX, 321 p. : ill. ; 24 cm. ISBN : 978-1-119-79876-7 Ref. Bibliogr. en fin de chapitres. - Index Langues : Anglais ( eng)
| Mots-clés : |
Artificial intelligence -- Industrial applications
Industry 4.0
5G mobile communication systems
Intelligence artificielle -- Applications industrielles
Industrie
Communications mobiles 5G |
| Index. décimale : |
004.896 Intelligence artificielle dans les systèmes industriels |
| Résumé : |
Artificial Intelligence in Industry 4.0 and 5G Technology Explores innovative and value-added solutions for application problems in the commercial, business, and industry sectors As the pace of Artificial Intelligence (AI) technology innovation continues to accelerate, identifying the appropriate AI capabilities to embed in key decision processes has never been more critical to establishing competitive advantage. New and emerging analytics tools and technologies can be configured to optimize business value, change how an organization gains insights, and significantly improve the decision-making process across the enterprise. Artificial Intelligence in Industry 4.0 and 5G Technology helps readers solve real-world technological engineering optimization problems using evolutionary and swarm intelligence, mathematical programming, multi-objective optimization, and other cutting-edge intelligent optimization methods. Contributions from leading experts in the field present original research on both the theoretical and practical aspects of implementing new AI techniques in a variety of sectors, including Big Data analytics, smart manufacturing, renewable energy, smart cities, robotics, and the Internet of Things (IoT). Presents detailed information on meta-heuristic applications with a focus on technology and engineering sectors such as smart manufacturing, smart production, innovative cities, and 5G networks. Offers insights into the use of metaheuristic strategies to solve optimization problems in business, economics, finance, and industry where uncertainty is a factor. Provides guidance on implementing metaheuristics in different applications and hybrid technological systems. Describes various AI approaches utilizing hybrid meta-heuristics optimization algorithms, including meta-search engines for innovative research and hyper-heuristics algorithms for performance measurement. Artificial Intelligence in Industry 4.0 and 5G Technology is a valuable resource for IT specialists, industry professionals, managers and executives, researchers, scientists, engineers, and advanced students an up-to-date reference to innovative computing, uncertainty management, and optimization approaches. |
| Note de contenu : |
Summary :
1. Dynamic Key-based Biometric End-User Authentication Proposal for IoT in Industry
2. Decision Support Methodology for Scheduling Orders in Additive Manufacturing
3. Significance of Consuming 5G-Built Artificial Intelligence in Smart Cities
4. Neural Network Approach to Segmentation of Economic Infrastructure Objects on High-Resolution Satellite Images
5. The Impact of Data Security on the Internet of Things
6. Sustainable Renewable Energy and Waste Management on Weathering Corporate Pollution
7. Adam Adaptive Optimization Method for Neural Network Models Regression in Image Recognition Tasks
8. Application of Integer Programming in Allocating Energy Resources in Rural Africa
9. Feasibility of Drones as the Next Step in Innovative Solution for Emerging Society
10. Designing a Distribution Network for a Soda Company: Formulation and Efficient Solution Procedure
11. Machine Learning and MCDM Approach to Characterize Student Attrition in Higher Education
12. A Concise Review on Recent Optimization and Deep Learning Applications in Blockchain Technology
13. Inventory Routing Problem with Fuzzy Demand and Deliveries with Priority
14. Comparison of Defuzzification Methods for Project Selection
15. Re-Identification-Based Models for Multiple Object Tracking |
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