Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition

An approach to determine carbon emission reduction target allocation based on the particle swarm optimization (PSO) algorithm, fuzzy c-means (FCM) clustering algorithm, and Shapley decomposition (PSO–FCM–Shapley) is proposed in this study. The method decomposes total carbon emissions into an interac...

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Veröffentlicht in:	Energy policy Jg. 66; S. 630 - 644
Hauptverfasser:	Yu, Shiwei, Wei, Yi-Ming, Wang, Ke
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 01.03.2014 Elsevier Elsevier Science Ltd
Schlagworte:	Air pollution caused by fuel industries Algorithms Allocation Applied sciences Carbon Carbon dioxide Carbon dioxide emissions Carbon emission reduction Cardinality Case studies China China (People's Republic) Climatology. Bioclimatology. Climate change Cluster analysis Clustering Cost and standard of living Decomposition Earth, ocean, space Economic development Emission standards Emissions Emissions control emissions factor Endowments Energy Energy development Energy economics Energy. Thermal use of fuels Exact sciences and technology External geophysics Function words Fuzzy logic General, economic and professional studies General. Regulations. Norms. Economy greenhouse gas emissions Growth rate Industry Meteorology Methodology. Modelling Optimization Optimization algorithms Provinces Residential areas Shapley value decomposition Standard of living Studies Targets allocation Value value added China Targets allocation Shapley value decomposition Carbon emission reduction
ISSN:	0301-4215, 1873-6777
Online-Zugang:	Volltext
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