Advances of artificial intelligence in a green energy environment:
Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy eng...
Gespeichert in:
| Weitere Verfasser: | , , , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
London
Elsevier, AP, Academic Press
[2022]
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| Schlagworte: | |
| Zusammenfassung: | Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy.Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.- Looks at new techniques in artificial intelligence (AI) reducing the dimension of data coverage worldwide- Chapters include AI methodologies using enhanced hybrid swarm-based optimization algorithms- Includes flowchart diagrams for exampling optimizing techniques |
| Beschreibung: | 1. Application of some ways to intensify the process of anaerobic bioconversion of organic matter; 2. Disasters impact assessment based on socioeconomic approach; 3. Uninterruptible power supply system of the consumer, reducing peak network loads; 4. Optimization of the anaerobic conversion of green biomass into volatile fatty acids for further production of high-calorie liquid fuel; 5. Life cycle cost and life cycle assessment: an approximation to understand the real impacts of the Electricity Supply Industry; 6. Comparison of open access multiobjective optimization software tools for standalone hybrid renewable energy systems; 7. Optimization of the process of anaerobic processing of organic waste in biogas plants through the use of a vortex layer apparatus; 8. Search of regularities in data: optimality, validity, and interpretability; 9. Artificial intelligence techniques for modeling of wind energy harvesting systems: a comparative analysis; 10. Human paradigm and reliability for aggregate production planning under uncertainty; 11. Artificial intelligenceebased intelligent geospatial analysis in disaster management; 12. Optimizing the daily use of limited solar panels in closely located rural schools in Zimbabwe; 13. Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics; 14. Hybrid optimization and artificial intelligence applied to energy systems: a review; 15. A brief literature review of quantitative models for sustainable supply chain management; 16. Optimized designing spherical void structures in 3D domains; 17. Swarm-based intelligent strategies for charging plug-in hybrid electric vehicles |
| Beschreibung: | xxvii, 385 Seiten Illustrationen, Diagramme, Karten 229 mm |
| ISBN: | 9780323897853 |
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| 520 | |a Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy.Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.- Looks at new techniques in artificial intelligence (AI) reducing the dimension of data coverage worldwide- Chapters include AI methodologies using enhanced hybrid swarm-based optimization algorithms- Includes flowchart diagrams for exampling optimizing techniques | ||
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| institution | BVB |
| isbn | 9780323897853 |
| language | English |
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| spelling | Advances of artificial intelligence in a green energy environment edited by Pandian Vasant, Joshua Thomas, Elias Munapo and Gerhard-Wilhelm Weber London Elsevier, AP, Academic Press [2022] xxvii, 385 Seiten Illustrationen, Diagramme, Karten 229 mm txt rdacontent n rdamedia nc rdacarrier 1. Application of some ways to intensify the process of anaerobic bioconversion of organic matter; 2. Disasters impact assessment based on socioeconomic approach; 3. Uninterruptible power supply system of the consumer, reducing peak network loads; 4. Optimization of the anaerobic conversion of green biomass into volatile fatty acids for further production of high-calorie liquid fuel; 5. Life cycle cost and life cycle assessment: an approximation to understand the real impacts of the Electricity Supply Industry; 6. Comparison of open access multiobjective optimization software tools for standalone hybrid renewable energy systems; 7. Optimization of the process of anaerobic processing of organic waste in biogas plants through the use of a vortex layer apparatus; 8. Search of regularities in data: optimality, validity, and interpretability; 9. Artificial intelligence techniques for modeling of wind energy harvesting systems: a comparative analysis; 10. Human paradigm and reliability for aggregate production planning under uncertainty; 11. Artificial intelligenceebased intelligent geospatial analysis in disaster management; 12. Optimizing the daily use of limited solar panels in closely located rural schools in Zimbabwe; 13. Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics; 14. Hybrid optimization and artificial intelligence applied to energy systems: a review; 15. A brief literature review of quantitative models for sustainable supply chain management; 16. Optimized designing spherical void structures in 3D domains; 17. Swarm-based intelligent strategies for charging plug-in hybrid electric vehicles Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy.Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.- Looks at new techniques in artificial intelligence (AI) reducing the dimension of data coverage worldwide- Chapters include AI methodologies using enhanced hybrid swarm-based optimization algorithms- Includes flowchart diagrams for exampling optimizing techniques bicssc Vasant, Pandian 1961- (DE-588)1045112240 edt Thomas, J. Joshua 1973- (DE-588)1222058235 edt Munapo, Elias (DE-588)1253089221 edt Weber, Gerhard-Wilhelm 1960- (DE-588)113368178 edt |
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| title | Advances of artificial intelligence in a green energy environment |
| title_auth | Advances of artificial intelligence in a green energy environment |
| title_exact_search | Advances of artificial intelligence in a green energy environment |
| title_exact_search_txtP | Advances of artificial intelligence in a green energy environment |
| title_full | Advances of artificial intelligence in a green energy environment edited by Pandian Vasant, Joshua Thomas, Elias Munapo and Gerhard-Wilhelm Weber |
| title_fullStr | Advances of artificial intelligence in a green energy environment edited by Pandian Vasant, Joshua Thomas, Elias Munapo and Gerhard-Wilhelm Weber |
| title_full_unstemmed | Advances of artificial intelligence in a green energy environment edited by Pandian Vasant, Joshua Thomas, Elias Munapo and Gerhard-Wilhelm Weber |
| title_short | Advances of artificial intelligence in a green energy environment |
| title_sort | advances of artificial intelligence in a green energy environment |
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