國立虎尾科技大學 |

Artificial Intelligence in Renewable Energetic Systems = Smart Sustainable Energy Systems /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Artificial Intelligence in Renewable Energetic Systems/ edited by Mustapha Hatti.
Reminder of title:	Smart Sustainable Energy Systems /
other author:	Hatti, Mustapha.
Description:	XII, 531 p. 420 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-73192-6
ISBN:	9783319731926

Artificial Intelligence in Renewable Energetic Systems = Smart Sustainable Energy Systems /
Artificial Intelligence in Renewable Energetic SystemsSmart Sustainable Energy Systems /[electronic resource] :edited by Mustapha Hatti. - 1st ed. 2018. - XII, 531 p. 420 illus.online resource. - Lecture Notes in Networks and Systems,352367-3370 ;. - Lecture Notes in Networks and Systems,1.

NPC Multilevel Inverters Advanced Conversion Technology in APF -- Optimization Study of Hybrid Renewable Energy System in Autonomous Site -- Ensemble of Support Vector Methods to Estimate Global Solar Radiation In Algeria -- Study of percentage effect of Polymer blends system on physical properties using MM/QM approach -- Optimization and characterization of Nanowires Semiconductor based-Solar Cells -- Using Phase Change Materials (PCMs) to reduce energy consumption in buildings -- Optimization of Copper Indium Gallium Diselenide Thin Film Solar Cell (CIGS).

This book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22–24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of and offers the possibility of transforming society. Taking advantage of the growing power of the microprocessor makes the complexity of renewable energy systems accessible, especially since the algorithms of artificial intelligence make it possible to take relevant decisions or even reveal unsuspected trends in the management and optimization of renewable energy flows. The book enables those working on energy systems and those dealing with models of artificial intelligence to combine their knowledge and their intellectual potential for the benefit of the scientific community and humanity.

ISBN: 9783319731926

Standard No.: 10.1007/978-3-319-73192-6doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Artificial Intelligence in Renewable Energetic Systems = Smart Sustainable Energy Systems /
LDR:03109nam a22003975i 4500 001 994888
003 DE-He213
005 20200704152524.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319731926 $9 978-3-319-73192-6
024 7 $a 10.1007/978-3-319-73192-6 $2 doi
035 $a 978-3-319-73192-6
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Artificial Intelligence in Renewable Energetic Systems $h [electronic resource] : $b Smart Sustainable Energy Systems / $c edited by Mustapha Hatti.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a XII, 531 p. 420 illus. $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 Lecture Notes in Networks and Systems, $x 2367-3370 ; $v 35
505 0 $a NPC Multilevel Inverters Advanced Conversion Technology in APF -- Optimization Study of Hybrid Renewable Energy System in Autonomous Site -- Ensemble of Support Vector Methods to Estimate Global Solar Radiation In Algeria -- Study of percentage effect of Polymer blends system on physical properties using MM/QM approach -- Optimization and characterization of Nanowires Semiconductor based-Solar Cells -- Using Phase Change Materials (PCMs) to reduce energy consumption in buildings -- Optimization of Copper Indium Gallium Diselenide Thin Film Solar Cell (CIGS).
520 $a This book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22–24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of and offers the possibility of transforming society. Taking advantage of the growing power of the microprocessor makes the complexity of renewable energy systems accessible, especially since the algorithms of artificial intelligence make it possible to take relevant decisions or even reveal unsuspected trends in the management and optimization of renewable energy flows. The book enables those working on energy systems and those dealing with models of artificial intelligence to combine their knowledge and their intellectual potential for the benefit of the scientific community and humanity.
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 0 $a Renewable energy resources. $3 563364
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Renewable and Green Energy. $3 683875
700 1 $a Hatti, Mustapha. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1202406
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319731919
776 0 8 $i Printed edition: $z 9783319731933
830 0 $a Lecture Notes in Networks and Systems, $x 2367-3370 ; $v 1 $3 1267315
856 4 0 $u https://doi.org/10.1007/978-3-319-73192-6
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)