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Hybrid neural networks for gasoline blending system modeling

contributor authorWen Yu , Xiaoou Li
date accessioned2020-03-12T23:23:51Z
date available2020-03-12T23:23:51Z
date issued2014
identifier other6889480.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1110023?show=full
formatgeneral
languageEnglish
publisherIEEE
titleHybrid neural networks for gasoline blending system modeling
typeConference Paper
contenttypeMetadata Only
identifier padid8278694
subject keywordscadmium compounds
subject keywordscopper compounds
subject keywordsgallium compounds
subject keywordsindium compounds
subject keywordsrecycling
subject keywordssolar cells
subject keywordsCdTe
subject keywordsCu(GaIn)Se
subject keywordsPV systems
subject keywordsSi
subject keywordsbroken solar cells
subject keywordscrystalline silicon silver
subject keywordseconomic PV waste recycling
subject keywordsend-of-life strategy
subject keywordsfloat glass production
subject keywordsintegrated approach
subject keywordslaw encouraging closed-loop economy
subject keywordspatterned silicon wafers
subject keywordsphotovoltaic cells
subject keywordsphotovoltaic manufacturing waste
subject keywordsphotovoltaic panel
subject keywordsproduction scrap
subject keywordsrare metals
subject keywordsraw materials
subject keywordsthin film photovoltaic waste
subject keywordsuniversal r
identifier doi10.1109/PVSC.2014.6925488
journal titleeural Networks (IJCNN), 2014 International Joint Conference on
filesize4265003
citations0


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