000 03666nam a22005295i 4500
001 978-3-319-73192-6
003 DE-He213
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008 180312s2018 sz | s |||| 0|eng d
020 _a9783319731926
_9978-3-319-73192-6
024 7 _a10.1007/978-3-319-73192-6
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aArtificial Intelligence in Renewable Energetic Systems
_h[electronic resource] :
_bSmart Sustainable Energy Systems /
_cedited by Mustapha Hatti.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXII, 531 p. 420 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Networks and Systems,
_x2367-3389 ;
_v35
505 0 _aNPC 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 _aThis 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 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 0 _aRenewable energy sources.
_94906
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aRenewable Energy.
_913722
700 1 _aHatti, Mustapha.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_953331
710 2 _aSpringerLink (Online service)
_953332
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319731919
776 0 8 _iPrinted edition:
_z9783319731933
830 0 _aLecture Notes in Networks and Systems,
_x2367-3389 ;
_v35
_953333
856 4 0 _uhttps://doi.org/10.1007/978-3-319-73192-6
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79130
_d79130