LEADER 02028oam 2200589 450 001 9910715182503321 005 20201209113011.0 035 $a(CKB)5470000002508186 035 $a(OCoLC)869564746 035 $a(EXLCZ)995470000002508186 100 $a20140131d2001 ua 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 04$aThe impact of new generation cooperatives on their communities /$fUnited States Department of Agriculture, Rural Business-Cooperative Service 210 1$aWashington, D.C. :$cUnited States Department of Agriculture, Rural Business-Cooperative Service,$d[2001?] 215 $a1 online resource (iii, 86 pages) $cillustrations, maps, forms 225 1 $aRBS research report ;$v177 320 $aIncludes bibliographical references. 606 $aAgriculture, Cooperative$zMiddle West$vCase studies 606 $aProducer cooperatives$zMiddle West$vCase studies 606 $aRural development$zMiddle West$vCase studies 606 $aAgriculture, Cooperative$2fast 606 $aEconomic history$2fast 606 $aProducer cooperatives$2fast 606 $aRural development$2fast 607 $aMiddle West$xEconomic conditions 607 $aMiddle West$2fast 608 $aCase studies.$2lcgft 608 $aCase studies.$2fast 615 0$aAgriculture, Cooperative 615 0$aProducer cooperatives 615 0$aRural development 615 7$aAgriculture, Cooperative. 615 7$aEconomic history. 615 7$aProducer cooperatives. 615 7$aRural development. 712 02$aUnited States.$bRural Business/Cooperative Service, 801 0$bGPO 801 1$bGPO 801 2$bOCLCF 801 2$bDIBIB 801 2$bGILDS 801 2$bINT 801 2$bOCLCQ 801 2$bGPO 906 $aBOOK 912 $a9910715182503321 996 $aThe impact of new generation cooperatives on their communities$93535461 997 $aUNINA LEADER 02742nam 22005415 450 001 9911034939903321 005 20251020130402.0 010 $a981-9517-82-6 024 7 $a10.1007/978-981-95-1782-4 035 $a(MiAaPQ)EBC32364747 035 $a(Au-PeEL)EBL32364747 035 $a(CKB)41689402500041 035 $a(DE-He213)978-981-95-1782-4 035 $a(EXLCZ)9941689402500041 100 $a20251020d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData-driven Optimization and Control for Autonomous Energy Systems /$fby Gang Wang, Jian Sun, Jie Chen 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (259 pages) 225 1 $aEnergy Series 311 08$a981-9517-81-8 327 $aIntroduction -- State Estimation via Composite Optimization -- State Estimation from Rank One Measurements -- State Estimation and Forecasting via Deep Unrolled Neutral Networks -- Data Graph Prior for State Estimation -- Stochastic Optimization -- Conclusion. 330 $aThis book introduces a pioneering framework for monitoring and controlling autonomous energy systems, distinguished by its use of physics-informed deep neural networks. These networks provide accurate estimations and forecasts, interlacing with advanced composite optimization algorithms to simplify the complex processes of state estimation. This approach not only boosts operational efficiency but also maximizes flexibility through a data-driven methodology integrated with physics-based principles. The framework leverages the power of neural networks to define the intricate relationship between system states and control policies, offering precise, robust control strategies that adapt to dynamically changing system conditions. This book is essential reading for professionals looking to enhance the performance and flexibility of energy systems through cutting-edge technology. 410 0$aEnergy Series 606 $aElectric power production 606 $aAutomation 606 $aMechanical Power Engineering 606 $aAutomation 615 0$aElectric power production. 615 0$aAutomation. 615 14$aMechanical Power Engineering. 615 24$aAutomation. 676 $a621.31 700 $aWang$b Gang$01853399 701 $aSun$b Jian$01834768 701 $aChen$b Jie$01299851 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911034939903321 996 $aData-Driven Optimization and Control for Autonomous Energy Systems$94449508 997 $aUNINA