Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization

Applied Energy

Volumn 92, Issue , 2012, Pages 552-562

  Yu, Shiwei ^a,b   Wei, Yi Ming ^b   Fan, Jingli ^b   Zhang, Xian ^b   Wang, Ke ^b  

^a CHINA UNIVERSITY OF GEOSCIENCES   (China)

^b BEIJING INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Carbon emission; Characteristics; Fuzzy C means cluster; Mitigation policy

Indexed keywords

CARBON DIOXIDE; CLUSTERING ALGORITHMS; FUZZY CLUSTERING; FUZZY SYSTEMS;

CARBON EMISSIONS; CHARACTERISTICS; CLUSTERING METHODS; CLUSTERING RESULTS; EMISSION CHARACTERISTICS; EMISSION INTENSITY; EMISSION REDUCTION; FUZZY C MEAN; FUZZY C-MEANS; GLOBAL CAPACITY; IMPROVED FUZZY CLUSTERING; MEMBERSHIP GRADE; MITIGATION POLICIES; OPTIMAL CLUSTER NUMBER; PER CAPITA; PER UNIT; REGIONAL CHARACTERISTICS;

PARTICLE SWARM OPTIMIZATION (PSO);

ALGORITHM; CARBON DIOXIDE; CARBON EMISSION; CLUSTER ANALYSIS; FUZZY MATHEMATICS; MITIGATION; OPTIMIZATION; POLICY ANALYSIS;

CHINA;

EID: 84055224176     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2011.11.068     Document Type: Article

References (36)

1. Akins M.J., Morrison A.S., Walmsleym R.W. Carbon emission pinch analysis (CEPA) for emission reduction in the New Zealand electricity sector. Appl Energy 2010, 87(3):982-987.
2. Sharma S.S. Determinants of carbon dioxide emission: empirical evidence from 69 countries. Appl Energy 2011, 88(1):376-382.
3. 2 emission in China 1997-2007. Energy Policy 2011, 10.1016/j.enpol.2011.05.02.
4. Yue C., Hu X., He C., et al. Provincial carbon emission and carbon intensity in China from 1995 to 2007 (Carbon Emission and Social Development, III). Acta Scientiarum Naturalium Universitatis Pekinensis 2010, 46(4):510-516. [in Chinese].
5. 2 emission in China: a regional comparative analysis. Ecol Econ 2009, 69(1):145-154.
6. Ma J., Chen Z., You J. Spatial econometric analysis on China's provincial primary energy-related carbon dioxide emission. Technol Econ 2010, 29(12):62-67. [in Chinese].
7. 2 emission in China. Ecol Environ 2006, 15(5):1029-1034. [in Chinese].
8. Wei Y.-M., Liu L.-C., Fang Y. China energy report (2008): carbon emission 2008, Scientific Press, Beijing, [in Chinese].
9. He J., Li S. Carbon reduction and regional economy. Manage Rev 2010, 22(6):9-16. [in Chinese].
10. Wang R., Liu W., Xiao L., et al. Path towards achieving of China's 2020 carbon emission reduction target - a discussion of low-carbon energy policies at province level. Energy Policy 2011, 39(5):2740-2747.
11. Yang G., Tang Z., Shi H., et al. Regional differences of carbon dioxide emission in China and emission-reduction policy recommendations. Adv Climate Change Res 2011, 7(1):35-40. [in Chinese].
12. Gao W., Jiang W., Xie H. Effect of economic development on energy carbon emission distribution. J Liaoning Tech Univ (Nat Sci) 2009, 28(2):296-299. [in Chinese].
13. 2 emissions in China. Resour Sci 2010, 32(2):211-217. [in Chinese].
14. Wang Q., Zhou P., Zhou D. Efficiency measurement with carbon dioxide emissions: the case of China. Appl Energy 2011, 10.1016/j.apenergy.2011.02.02.
15. Yue R., Zhu Y. Provincial cluster analysis on China's energy carbon emission from 1990 to 2007. Technol Econ 2010, 29(3):40-45.
16. Bezdek J.C. Pattern recognition with fuzzy objective function algorithms 1981, Plenum, New York.
17. Pan T.-H., Shieh S.-S., Jang S.-S., et al. Statistical multi-model approach for performance assessment of cooling tower. Energy Convers Manage 2011, 52(2):1377-1385.
18. Besheer A.H., Emara H.M., Abdel Aziz M.M. Wind energy conversion system regulation via LMI fuzzy pole cluster approach. Electric Power Sys Res 2009, 79(4):531-538.
19. Gómez M., López A., Jurado F. Optimal placement and sizing from standpoint of the investor of photovoltaics grid-connected systems using binary particle swarm optimization. Appl Energy 2010, 87(6):1911-1918.
20. Rezaee B. A cluster validity index for fuzzy clustering. Fuzzy Sets Sys 2010, 161(23):3014-3025.
21. Zhang B., Yao N., Liu X.-M. Preliminary fuzzy clustering analysis on carbon emission in different provinces of China. China Popul Resour Environ 2011, 21(1):54-56. [in Chinese].
22. Groll L., Jakel J. A new convergence proof of fuzzy C-means. IEEE Trans Fuzzy Sys 2005, 13(5):717-720.
23. Juang C., Hsiao C.-M., Hsu C.-H. Hierarchical cluster-based multispecies particle-swarm optimization for fuzzy-system optimization. IEEE Trans Fuzzy Syst 2010, 18(1):14-26.
24. Filho FM, Gomide F. Fuzzy clustering in fitness estimation models for genetic algorithms and applications. In: Proceedings of IEEE international conference on fuzzy systems; 2006. p. 1388-95.
25. Saha S., Bandyopadhyay S. A new point symmetry based fuzzy genetic clustering technique for automatic evolution of clusters. Inf Sci 2009, 179(19):3230-3246.
26. Yoon J-W, Cho S-B. An efficient genetic algorithm with fuzzy C-means clustering for traveling salesman problem. In: Proceedings of IEEE congress on evolutionary computation 2011. p. 1452-6.
27. Runkler TA, Katz C. Fuzzy clustering by particle swarm optimization. In: Proceedings of 2006 IEEE international conference on fuzzy systems, Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada.
28. Huang Y.K. A hybrid particle swarm optimization approach for clustering and classification of datasets. Knowl-Based Syst 2011, 24(3):420-426.
29. Kuo R.J., Wang M.J., Huang T.W. An application of particle swarm optimization algorithm to clustering analysis. Soft computing - a fusion of foundations. Method Appl 2010, 15(3):533-542.
30. IPCC. Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change, In: Solomon S, et al., editors. Cambridge University Press, Cambridge, UK; 2007.
31. Bezdek J.C., Pal N.R. Some new indices of cluster validity. IEEE Trans Sys, Man, Cyber 1998, 28(3):301-315.
32. Zhu K., Su S., Li J. Optimal number of clusters and the best partition in fuzzy C-mean. Sys Eng - Theory Practice 2005, 25(3):52-61. [in Chinese].
33. Hsieh S.-T., Sun T., Liu C.-C. Potential offspring production strategies: an improved genetic algorithm for global numerical optimization. Expert Sys Appl 2009, 36(8):11088-11098.
34. Kennedy J, Eberhart RC. Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks; 1995. p. 1942-8.
35. Yu S., Zhu K., Guo S. A hybrid MPSO-BP structure adaptive algorithm for RBFNs. Neural Comput Appl 2009, (18):769-779.
36. Unler A., Murat A. A discrete particle swarm optimization method for feature selection in binary classification problems. Eur J Oper Res 2010, 206(3):528-539.