Decision making using AI in energy and sustainability [electronic resource] : methods and models for policy and practice / Gülgün Kayakutlu, M. Özgür Kayalica, editors.
Kayakutlu, Gülgün, editor.; Kayalica, M. Özgür, editor.
2023
TJ808 .D43 2023
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Decision making using AI in energy and sustainability [electronic resource] : methods and models for policy and practice / Gülgün Kayakutlu, M. Özgür Kayalica, editors.
ISBN 9783031383878 (electronic bk.)
3031383877 (electronic bk.)
3031383869
9783031383861
DOI https://doi.org/10.1007/978-3-031-38387-8
Imprint Cham, Switzerland : Springer, [2023]
Language English
Description 1 online resource (xi, 312 pages) : illustrations
Other Standard Identifiers 10.1007/978-3-031-38387-8 doi
Call Number TJ808 .D43 2023
Dewey Decimal Classification 333.79/4
Summary Artificial intelligence (AI) has a huge impact on science and technology, including energy, where access to resources has been a source of geopolitical conflicts. AI can predict the demand and supply of renewable energy, optimize efficiency in energy systems, and improve the management of natural energy resources, among other things. This book explores the use of AI tools for improving the management of energy systems and providing sustainability with smart cities, smart facilities, smart buildings, smart transportation, and smart houses. Featuring research from International Federation for Information Processing's (IFIP) AI in Energy and Sustainability working group, this book provides new models and algorithms for AI applications in energy and sustainability fields. Any short-term, mid-term and long-term forecasting, optimization models, trend foresights and prescriptions based on scenarios are studied in the energy world and the smart systems for sustainability. The contents of this book are valuable for energy researchers, academics, scholars, practitioners and policy makers.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 25, 2023).
Added Author Kayakutlu, Gülgün, editor.
Kayalica, M. Özgür, editor.
Series Applied innovation and technology management.
Available in Other Form Print version: 9783031383861
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
1. Climate change Can AI help understanding and more effective facing of various interrelated impacts?- 2. A methodology for linking the Energy-related Policies of the European Green Deal to the 17 SDGs using Machine Learning
3. Single-valued neutrosophic CRITIC-based ARAS method for the assessment of sustainable circular supplier selection
4. Linguistic-Based MCDM Approach for Climate Change Risk Evaluation Methodology
5. Creating a Net-Zero Carbon Emission Scenario Using OSeMOSYS for the Power Sector of Turkey
6. Prediction of Downward Surface Solar Radiation Using Particle Swarm Optimization and Neural Networks
7. Electricity Demand Prediction: Case of Turkey
8. The Impact Of The Wind Energy Power Forecast Accuracy On The Price Of Electricity
9. The Power of Combination Models in Energy Demand Forecasting
10. Data-driven state classification for energy modeling of machine tools using power signals and part-program information
11. Energy Efficiency Optimization Application in Food Production using IIOT based Machine Learning
12. Hype: a data-driven tool for smart city profile (SCP) discrimination
13. An Integrated Hesitant Fuzzy Linguistic MCDM Methods to Assess Smart City Solutions
14. Presence of Renewable Resources in a Smart City for Supplying Clean and Sustainable Energy
15. Syrian Household Energy Consumption Behavior Analysis In Turkey: Bayesian Belief Network
16. Informativeness in Twitter Textual Contents for Farmer-centric Pest Monitoring
17. A Multi-Criteria Decision-Making Model for Technology Selection in Renewable-Based Residential Microgrids
18. Energy Management in Power-Split Hybrid Electric Vehicles Using Fuzzy Logic Controller.

Browse Subjects

Show more subjects...

Statistics

from
to
Export