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Record Nr. |
UNINA9910731479003321 |
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Autore |
Manshahia Mukhdeep Singh |
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Titolo |
Advances in Artificial Intelligence for Renewable Energy Systems and Energy Autonomy / / edited by Mukhdeep Singh Manshahia, Valeriy Kharchenko, Gerhard-Wilhelm Weber, Pandian Vasant |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (302 pages) |
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Collana |
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EAI/Springer Innovations in Communication and Computing, , 2522-8609 |
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Altri autori (Persone) |
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KharchenkoValeriy |
WeberGerhard Wilhelm |
VasantPandian |
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Disciplina |
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Soggetti |
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Renewable energy sources |
Artificial intelligence |
Computational intelligence |
Renewable Energy |
Artificial Intelligence |
Computational Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1. General Approaches to Assessing Electrical Load of Agro-Industrial Complex Facilities When Justifying the Parameters of the Photovoltaic Power System -- Chapter 2. RBFNN for MPPT Controller in Wind Energy Harvesting System -- Chapter 3. Simulation Optimum Performance All-Wheels Plug-In Hybrid Electric Vehicle -- Chapter 4. Artificial Intelligence application to flexibility provision in energy management system: a survey -- Chapter 5. Machine Learning Applications for Renewable Energy Systems -- Chapter 6. New Technologies and Equipment For Smelting Technical Silicon -- Chapter 7. Reconfiguration of distribution network considering photovoltaic system placement based on metaheuristic algorithms -- Chapter 8. Technology of Secondary Cast Polycrystalline Silicon And Its Application In The Production Of Solar Cells -- Chapter 9. Machine Learning |
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Applications for Renewable based Energy Systems -- Chapter 10. Bi-Objective Optimal Scheduling of Smart Homes Appliances using Artificial Intelligence -- Chapter 11. Optimal placement of photovoltaic systems and wind turbines in distribution systems by using Northern Goshawk Optimization algorithm -- Chapter 12. Granulated silicon and thermal energy converters on its basis -- Chapter 13. Security Constrained Unit Commitment with Wind Energy Resource using Universal Generating Function. |
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Sommario/riassunto |
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This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy. Based on sustainability as a fundamental factor for intelligent computing; Focuses on the role AI playsin smart living, energy transition, and sustainable development; Covers a broad range of green energy-related topics. |
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2. |
Record Nr. |
UNINA9911033780103321 |
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Autore |
Simposio sull'architettura di Noto : <1977 |
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Titolo |
Atti del Simposio sull'architettura di Noto / [a cura di] Corrado Fianchino |
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Pubbl/distr/stampa |
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Siracusa, : E.P.T., stampa 1979 |
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Descrizione fisica |
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Livello bibliografico |
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3. |
Record Nr. |
UNINA9911035158603321 |
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Autore |
Wen Wen |
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Titolo |
The Global Development of AI-Empowered Higher Education: Beyond the Horizon / / edited by Wen Wen, Yu Zhang |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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9789819690053 |
9789819690046 |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (243 pages) |
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Collana |
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Research in Chinese Education, , 2524-4779 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Educational technology |
Education - Data processing |
Education, Higher |
Digital Education and Educational Technology |
Computers and Education |
Higher Education |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Preface -- Executive Summary -- Chapter 1. The Evolution and Latest Trends of AI Technology -- Chapter 2. Learning and Teaching in AI-Empowered Higher Education -- Chapter 3. Ethical Challenges of AI-Empowered Higher Education -- Chapter 4. Applications and Student Perceptions of GenAI in Higher Education: Findings from International Pilot Studies -- Chapter 5. Nurturing AI Talent in Higher Education -- Chapter 6. Policy Directions with Alternative Frameworks for AI in Higher Education Institutions -- Acknowledgement. |
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Sommario/riassunto |
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This book provides a forward-looking and comprehensive examination of AI’s transformative impact on higher education. It explores the integration of AI in teaching, learning, and assessment with fresh insights into generative AI, artificial general intelligence (AGI), and their emerging roles in reshaping universities globally. Supported by case studies from 30 leading universities and empirical data from international surveys and interviews, the book stands apart by combining AI development trends with practical applications and ethical considerations. This book includes detailed discussions on AI's ethical challenges, including privacy, academic integrity, and the widening digital divide, all paired with real-world examples. A unique feature of the book is its in-depth exploration of AI talent development, outlining national strategies and institutional approaches that equip students with both AI literacy and advanced skills, establishing a new standard for cultivating future leaders in the AI era. With strategic policy recommendations, this book provides a roadmap for higher education institutions to navigate the rapidly evolving AI landscape. It highlights actionable frameworks for ensuring equitable access to technology, strengthening data security, and addressing biases in AI systems. Academics, policymakers, and education leaders will benefit from its forward-thinking approach to integrating AI while maintaining humanistic and ethical values in education. Designed for professionals in education and education policy, this book also serves as an essential guide for other readers looking to harness the power of AI in shaping the future of learning and teaching. |
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