FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4228996833> ?p ?o ?g. }

• W4228996833 endingPage "101378" @default.
• W4228996833 startingPage "101378" @default.
• W4228996833 abstract "Photovoltaic poverty alleviation project (PPAP) is one of China's essential targeted poverty alleviation projects. This study proposes a machine learning model and uses satellite images to evaluate the performance of PPAP in China. The trained deep convolutional neural network (DCNN) with transfer learning was first used to identify the scale of photovoltaic (PV) power stations. Then the PV power capacity for poverty alleviation and carbon emission mitigation were estimated. The results identified 38 large-scale centralized and approximately 5,063,293 m2PV power stations built in Jinzhai County, Anhui province, China, by November 2020. The main findings are as follows. (1) The power generation and carbon mitigation of PPAP in Jinzhai County is about 1.8×103 MWh and 1.389 Mt per year. (2) The PPAP in Jinzhai County can recover the total costs and get benefits within three years, at least after completion. (3) Dynamic subsidy policy is needed to prevent over-scale or excessive government investment in PPAP. (4) The utilization of PPAP needs to be strengthened to transform the current “blood transfusion type” of poverty alleviation that relies more on government subsidies into more sustainable “hematopoietic style” poverty alleviation. This study is of significance to more accurately and comprehensively evaluate the performance of PPAP and give better utilize the role of renewable energy in promoting energy conservation, carbon emission reduction, and economic development." @default.
• W4228996833 created "2022-05-08" @default.
• W4228996833 creator A5056457307 @default.
• W4228996833 creator A5071422468 @default.
• W4228996833 date "2022-06-01" @default.
• W4228996833 modified "2023-10-01" @default.
• W4228996833 title "Performance evaluation of China's photovoltaic poverty alleviation project using machine learning and satellite images" @default.
• W4228996833 cites W2004963276 @default.
• W4228996833 cites W2006662908 @default.
• W4228996833 cites W2056568601 @default.
• W4228996833 cites W2067247994 @default.
• W4228996833 cites W2261059368 @default.
• W4228996833 cites W2494424066 @default.
• W4228996833 cites W2513506629 @default.
• W4228996833 cites W2515526268 @default.
• W4228996833 cites W2563461056 @default.
• W4228996833 cites W2581746499 @default.
• W4228996833 cites W2746456090 @default.
• W4228996833 cites W2756291343 @default.
• W4228996833 cites W2791475284 @default.
• W4228996833 cites W2793282686 @default.
• W4228996833 cites W2793927960 @default.
• W4228996833 cites W2805386057 @default.
• W4228996833 cites W2808086296 @default.
• W4228996833 cites W2887914937 @default.
• W4228996833 cites W2889790220 @default.
• W4228996833 cites W2901106490 @default.
• W4228996833 cites W2904145953 @default.
• W4228996833 cites W2907955367 @default.
• W4228996833 cites W2908613846 @default.
• W4228996833 cites W2910603369 @default.
• W4228996833 cites W2912168812 @default.
• W4228996833 cites W2919115771 @default.
• W4228996833 cites W2954996726 @default.
• W4228996833 cites W2968231786 @default.
• W4228996833 cites W2980049357 @default.
• W4228996833 cites W3003155844 @default.
• W4228996833 cites W3014372673 @default.
• W4228996833 cites W3026137789 @default.
• W4228996833 cites W3027716283 @default.
• W4228996833 cites W3042306019 @default.
• W4228996833 cites W3044773400 @default.
• W4228996833 cites W3049000524 @default.
• W4228996833 cites W3093679004 @default.
• W4228996833 cites W3093803614 @default.
• W4228996833 cites W3105625590 @default.
• W4228996833 cites W3109100540 @default.
• W4228996833 cites W3116790507 @default.
• W4228996833 cites W3125397976 @default.
• W4228996833 doi "https://doi.org/10.1016/j.jup.2022.101378" @default.
• W4228996833 hasPublicationYear "2022" @default.
• W4228996833 type Work @default.
• W4228996833 citedByCount "3" @default.
• W4228996833 countsByYear W42289968332022 @default.
• W4228996833 countsByYear W42289968332023 @default.
• W4228996833 crossrefType "journal-article" @default.
• W4228996833 hasAuthorship W4228996833A5056457307 @default.
• W4228996833 hasAuthorship W4228996833A5071422468 @default.
• W4228996833 hasConcept C119599485 @default.
• W4228996833 hasConcept C127413603 @default.
• W4228996833 hasConcept C134560507 @default.
• W4228996833 hasConcept C138885662 @default.
• W4228996833 hasConcept C144133560 @default.
• W4228996833 hasConcept C162324750 @default.
• W4228996833 hasConcept C166957645 @default.
• W4228996833 hasConcept C17744445 @default.
• W4228996833 hasConcept C188573790 @default.
• W4228996833 hasConcept C189326681 @default.
• W4228996833 hasConcept C191935318 @default.
• W4228996833 hasConcept C199539241 @default.
• W4228996833 hasConcept C205649164 @default.
• W4228996833 hasConcept C27548731 @default.
• W4228996833 hasConcept C2778137410 @default.
• W4228996833 hasConcept C2778755073 @default.
• W4228996833 hasConcept C41291067 @default.
• W4228996833 hasConcept C41895202 @default.
• W4228996833 hasConcept C50522688 @default.
• W4228996833 hasConcept C552854447 @default.
• W4228996833 hasConcept C58640448 @default.
• W4228996833 hasConcept C84265765 @default.
• W4228996833 hasConcept C94625758 @default.
• W4228996833 hasConceptScore W4228996833C119599485 @default.
• W4228996833 hasConceptScore W4228996833C127413603 @default.
• W4228996833 hasConceptScore W4228996833C134560507 @default.
• W4228996833 hasConceptScore W4228996833C138885662 @default.
• W4228996833 hasConceptScore W4228996833C144133560 @default.
• W4228996833 hasConceptScore W4228996833C162324750 @default.
• W4228996833 hasConceptScore W4228996833C166957645 @default.
• W4228996833 hasConceptScore W4228996833C17744445 @default.
• W4228996833 hasConceptScore W4228996833C188573790 @default.
• W4228996833 hasConceptScore W4228996833C189326681 @default.
• W4228996833 hasConceptScore W4228996833C191935318 @default.
• W4228996833 hasConceptScore W4228996833C199539241 @default.
• W4228996833 hasConceptScore W4228996833C205649164 @default.
• W4228996833 hasConceptScore W4228996833C27548731 @default.
• W4228996833 hasConceptScore W4228996833C2778137410 @default.
• W4228996833 hasConceptScore W4228996833C2778755073 @default.
• W4228996833 hasConceptScore W4228996833C41291067 @default.

• next