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101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 13$aAn analysis of post-attack impacts and effects of learning parameters on vulnerability assessment of power grid /$fShuva Paul, Zhen Ni, and Fei Ding
210  1$aGolden, CO :$cNational Renewable Energy Laboratory,$d2020.
215   $a1 online resource (1 page) $ccolor illustrations
225 1 $aNREL/PO ;$v5D00-76118
300   $aPresented at the Innovative Smart Grid Technologies (ISGT 2020) North America, 17-20 February 2020, Washington, D.C.
606   $aElectric power systems$xProtection
606   $aElectric power systems$xComputer simulation
615  0$aElectric power systems$xProtection.
615  0$aElectric power systems$xComputer simulation.
700   $aPaul$b Shuva$01410153
712 02$aNational Renewable Energy Laboratory (U.S.),
801  0$bGPO
801  1$bGPO
906   $aBOOK
912   $a9910713951403321
996   $aAn analysis of post-attack impacts and effects of learning parameters on vulnerability assessment of power grid$93498332
997   $aUNINA