Advances of Artificial Intelligence in a Green Energy Environment
- 1st Edition - May 20, 2022
- Imprint: Academic Press
- Editors: Pandian Vasant, Joshua Thomas, Elias Munapo, Gerhard-Wilhelm Weber
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 8 9 7 8 5 - 3
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 8 8 5 7 4 - 4
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… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteAdvances 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
Primary market/audience (and market size, if known) :
Engineers, Scientists, Academicians, Researchers, Students, University officers, Governmental decision makers
Secondary market/audience:
Technicians, Research Officers, Post-Graduates, Under-Graduates, Policy Makers
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- About the editors
- Preface
- Acknowledgments
- Chapter 1. Application of some ways to intensify the process of anaerobic bioconversion of organic matter
- 1.1. Introduction
- 1.2. Methods for improving the process of methane digestion of manure and manure runoff and their analysis
- 1.3. Application results
- 1.4. Energy model
- 1.5. Conclusion
- Chapter 2. Disasters impact assessment based on socioeconomic approach
- 2.1. Introduction
- 2.2. Statistics and tendencies of natural and man-made disasters
- 2.3. Overview of institutions dealing with risk management
- 2.4. Promising approaches to decrease risks and losses caused by disasters
- 2.5. The issues of effective disaster countering organization
- 2.6. Socioeconomic approach to the estimations of risk dynamics
- 2.7. Conclusions
- Appendix A: An example of selecting the optimal list of prevention or mitigation measures
- Chapter 3. Uninterruptible power supply system of the consumer, reducing peak network loads
- 3.1 Introduction
- 3.2 Methodology of the work
- 3.3 Work results
- 3.4. Conclusions
- Chapter 4. Optimization of the anaerobic conversion of green biomass into volatile fatty acids for further production of high-calorie liquid fuel
- 4.1. Introduction
- 4.2. Experimental part and methods
- 4.3. Results and discussion
- 4.4. Conclusions
- Chapter 5. Life cycle cost and life cycle assessment: an approximation to understand the real impacts of the Electricity Supply Industry
- 5.1. Importance of Electricity Supply Industry
- 5.2. The economics of Electricity Supply Industry
- 5.3. The life cycle of Electricity Supply Industry
- 5.4. Importance of life cycle assessment of Electricity Supply Industry
- 5.5. Life cycle cost of Electricity Supply Industry
- 5.6. Mobilizing industry for a clean and circular economy
- Chapter 6. Comparison of open access multi-objective optimization software tools for standalone hybrid renewable energy systems
- 6.1. Introduction
- 6.2. Literature review
- 6.3. Open access multi-objective optimization tools
- 6.4. Case study
- 6.5. Conclusion
- Chapter 7. Optimization of the organic waste anaerobic digestion in biogas plants through the use of a vortex layer apparatus
- 7.1. Introduction
- 7.2. Anaerobic processing of organic waste: general characteristics of fermentation
- 7.3. Methods of preprocessing
- 7.4. Vortex layer apparatus
- 7.5. Application of the vortex layer apparatus in biogas plants
- 7.6. Conclusion
- Chapter 8. Search of regularities in data: optimality, validity, and interpretability
- 8.1. Introduction
- 8.2. Occam's razor principle for verification of parametric regression models
- 8.3. Occam's razor principle for verification of regression models based on optimal partitioning
- 8.4. Conclusion
- Chapter 9. Artificial intelligence techniques for modeling of wind energy harvesting systems: a comparative analysis
- 9.1. Introduction
- 9.2. Review of related works
- 9.3. Modeling of wind energy harvesting system
- 9.4. Maximum power point tracking system
- 9.5. Load side converter control
- 9.6. Results and discussion
- 9.7. Conclusion
- Chapter 10. Human paradigm and reliability for aggregate production planning under uncertainty
- 10.1. Introduction
- 10.2. Literature review
- 10.3. Discussion and conclusion
- Chapter 11. Artificial intelligence–based intelligent geospatial analysis in disaster management
- 11.1. Introduction
- 11.2. Related work
- 11.3. Proposed work
- 11.4. Performance analysis
- 11.5. Conclusion
- Chapter 12. Optimizing the daily use of limited solar panels in closely located rural schools in Zimbabwe
- 12.1. Introduction
- 12.2. Modeling the solar panel problem
- 12.3. TSP network features
- 12.4. Dummies and their use in elimination of subtours
- 12.5. Proposed algorithm for TSP
- 12.6. Other applications of the traveling salesman
- 12.7. Conclusions
- Chapter 13. Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics
- 13.1. Introduction
- 13.2. Economic load/emission dispatch
- 13.3. Bioenergy and biofuel supply chains
- 13.4. Sustainable capacity planning and optimization
- 13.5. Outlook
- Chapter 14. Hybrid optimization and artificial intelligence applied to energy systems: a review
- 14.1. Introduction
- 14.2. Stochastic programming
- 14.3. Optimization in energy systems
- 14.4. Conclusions
- Chapter 15. A brief literature review of quantitative models for sustainable supply chain management
- 15.1. Introduction
- 15.2. Theoretical foundation and literature reviews
- 15.3. Methodology
- 15.4. Results
- 15.5. Discussion
- 15.6. Conclusion
- Chapter 16. Optimized designing spherical void structures in 3D domains
- 16.1. Introduction
- 16.2. Problem formulation
- 16.3. Mathematical model
- 16.4. Mathematical model with balancing conditions
- 16.5. Numerical experiments
- 16.6. Conclusions
- Chapter 17. Swarm-based intelligent strategies for charging plug-in hybrid electric vehicles
- 17.1. Introductions
- 17.2. Problem formulation
- 17.3. Swarm-based intelligence approaches
- 17.4. Results and discussions
- 17.5. Conclusions
- Index
- Edition: 1
- Published: May 20, 2022
- No. of pages (Paperback): 414
- No. of pages (eBook): 414
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780323897853
- eBook ISBN: 9780323885744
PV
Pandian Vasant
Pandian Vasant is a Research Associate at MERLIN Research Centre, TDTU in Vietnam. He holds a PhD in Computational Intelligence, an MSc in Engineering Mathematics, and a BSc in Mathematics. His research interests include soft computing, hybrid optimization, holistic optimization, innovative computing, and applications.
Affiliations and expertise
Research Associate at MERLIN Research Centre, TDTU in VietnamJT
Joshua Thomas
J. Joshua Thomas is an Associate Professor at UOW Malaysia KDU Penang University College. He obtained his PhD (Intelligent Systems Techniques) from University Sains Malaysia, Penang, and master’s degree from Madurai Kamaraj University, India. He is working with deep learning algorithms, specially targeting on graph convolutional neural networks and bidirectional recurrent neural networks for drug target interaction and image tagging with embedded natural language processing. His work involves experimental research with software prototypes and mathematical modeling and design.
Affiliations and expertise
Associate Professor, UOW Malaysia KDU Penang University College, MalaysiaEM
Elias Munapo
Elias Munapo holds a BSc in Applied Mathematics, an MSc in Operations Research, and a PhD in Applied Mathematics, all from the National University of Science and Technology (N.U.S.T.) in Zimbabwe. Elias has vast experience in university education and has worked for five institutions of higher learning. He was a lecturer at Zimbabwe Open University, Chinhoyi University of Technology, and University of South Africa. He became a Senior Lecturer at the University of KwaZulu-Natal and then joined North West University as an Associate Professor in 2016 and has been appointed as a Professor since January 2019.rofessor
Affiliations and expertise
Professor, North West University, South AfricaGW
Gerhard-Wilhelm Weber
Gerhard-Wilhelm Weber is a Professor at Poznan University of Technology, Poznan, Poland, at Faculty of Engineering Management, in the Chair of Marketing and Economic Engineering. His research is on data mining, analytics, AI, machine learning, mathematics, operational research, finance, economics, optimization and optimal control, neuro-, bio-, and earth sciences, medicine, and development; he is involved in the organization of scientific life internationally.
Affiliations and expertise
Professor, Poznan University of Technology, PolandRead Advances of Artificial Intelligence in a Green Energy Environment on ScienceDirect