Advances on Computational Intelligence in Energy [E-Book] : The Applications of Nature-Inspired Metaheuristic Algorithms in Energy / edited by Tutut Herawan, Haruna Chiroma, Jemal H. Abawajy
Addressing the applications of computational intelligence algorithms in energy, this book presents a systematic procedure that illustrates the practical steps required for applying bio-inspired, meta-heuristic algorithms in energy, such as the prediction of oil consumption and other energy products....
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Full text |
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Personal Name(s): | Abawajy, Jemal H., editor |
Chiroma, Haruna, editor / Herawan, Tutut, editor | |
Edition: |
1st edition 2019. |
Imprint: |
Cham :
Springer,
2019
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Physical Description: |
XIV, 215 pages (online resource) |
Note: |
englisch |
ISBN: |
9783319698892 |
DOI: |
10.1007/978-3-319-69889-2 |
Series Title: |
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Green Energy and Technology
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Subject (LOC): |
- Basic descriptions of computational intelligence algorithms (single, hybrid, ensemble, integrated and etc
- Credible sources of energy datasets
- Applications of computational algorithms in energy
- Practical application of cuckoo search and neural network in the prediction of OECD oil consumption
- Hybrid of Fuzzy systems and particle swarm optimization in the forecasting gas flaring from oil consumption
- Forecasting of OECD gas flaring using Elman neural network and cuckoo search algorithm
- Artificial bee colony and neural network for the forecasting of Malaysia renewable energy
- Soft computing methods in the modelling of OECD carbon dioxide emission from petroleum consumption
- Modelling energy crises based on Soft computing
- The forecasting of WTI and Dubai crude oil prices benchmarks based on soft computing
- A new approach for the forecasting of IAEA energy
- Modelling of gasoline prices using fuzzy multi-criteria decision making
- Soft computing for the prediction of Australia petroleum consumption based on OECD countries
- Future research problems in the area of computational intelligence algorithms in energy. .