TY  - GEN
N2  - 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. Contributions include research findings, projects, surveying work and industrial experiences that describe significant advances in the applications of computational intelligence algorithms in energy. For easy understanding, the text provides practical simulation results, convergence and learning curves as well as illustrations and tables. Providing a valuable resource for undergraduate and postgraduate students alike, it is also intended for researchers in the fields of computational intelligence and energy.
AB  - 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. Contributions include research findings, projects, surveying work and industrial experiences that describe significant advances in the applications of computational intelligence algorithms in energy. For easy understanding, the text provides practical simulation results, convergence and learning curves as well as illustrations and tables. Providing a valuable resource for undergraduate and postgraduate students alike, it is also intended for researchers in the fields of computational intelligence and energy.
T1  - Advances on computational intelligence in energy :the applications of nature-inspired metaheuristic algorithms in energy /
AU  - Herawan, Tutut,
AU  - Chiroma, Haruna,
AU  - Abawajy, Jemal H.,
CN  - Q342
ID  - 898833
KW  - Computational intelligence.
KW  - Metaheuristics.
SN  - 9783319698892
SN  - 3319698893
TI  - Advances on computational intelligence in energy :the applications of nature-inspired metaheuristic algorithms in energy /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-69889-2
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-69889-2
ER  -