國立虎尾科技大學 |

Advances on Computational Intelligence in Energy = The Applications of Nature-Inspired Metaheuristic Algorithms in Energy /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advances on Computational Intelligence in Energy/ edited by Tutut Herawan, Haruna Chiroma, Jemal H. Abawajy.
其他題名:	The Applications of Nature-Inspired Metaheuristic Algorithms in Energy /
其他作者:	Herawan, Tutut.
面頁冊數:	XIV, 215 p.online resource. :
Contained By:	Springer Nature eBook
標題:	Energy systems. -
電子資源:	https://doi.org/10.1007/978-3-319-69889-2
ISBN:	9783319698892

Advances on Computational Intelligence in Energy = The Applications of Nature-Inspired Metaheuristic Algorithms in Energy /
Advances on Computational Intelligence in EnergyThe Applications of Nature-Inspired Metaheuristic Algorithms in Energy /[electronic resource] :edited by Tutut Herawan, Haruna Chiroma, Jemal H. Abawajy. - 1st ed. 2019. - XIV, 215 p.online resource. - Green Energy and Technology,1865-3529. - Green Energy and Technology,.

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. .

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.

ISBN: 9783319698892

Standard No.: 10.1007/978-3-319-69889-2doiSubjects--Topical Terms:

1253529
Energy systems.

LC Class. No.: TK1001-1841

Dewey Class. No.: 621.042

Advances on Computational Intelligence in Energy = The Applications of Nature-Inspired Metaheuristic Algorithms in Energy /
LDR:03377nam a22003975i 4500 001 1014187
003 DE-He213
005 20200705130517.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783319698892 $9 978-3-319-69889-2
024 7 $a 10.1007/978-3-319-69889-2 $2 doi
035 $a 978-3-319-69889-2
050 4 $a TK1001-1841
072 7 $a TH $2 bicssc
072 7 $a TEC031000 $2 bisacsh
072 7 $a TH $2 thema
082 0 4 $a 621.042 $2 23
245 1 0 $a Advances on Computational Intelligence in Energy $h [electronic resource] : $b The Applications of Nature-Inspired Metaheuristic Algorithms in Energy / $c edited by Tutut Herawan, Haruna Chiroma, Jemal H. Abawajy.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XIV, 215 p. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Green Energy and Technology, $x 1865-3529
505 0 $a 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. .
520 $a 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.
650 0 $a Energy systems. $3 1253529
650 0 $a Computational intelligence. $3 568984
650 0 $a Algorithms. $3 527865
650 0 $a Energy policy. $3 554736
650 0 $a Energy and state. $3 1197930
650 1 4 $a Energy Systems. $3 785876
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Energy Policy, Economics and Management. $3 784769
700 1 $a Herawan, Tutut. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1023167
700 1 $a Chiroma, Haruna. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1229395
700 1 $a Abawajy, Jemal H. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1067752
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319698885
776 0 8 $i Printed edition: $z 9783319698908
830 0 $a Green Energy and Technology, $x 1865-3529 $3 1254274
856 4 0 $u https://doi.org/10.1007/978-3-319-69889-2
912 $a ZDB-2-ENE
912 $a ZDB-2-SXEN
950 $a Energy (SpringerNature-40367)
950 $a Energy (R0) (SpringerNature-43717)