Combined Forecasting Model Based on the Rough Set to Predict the Chinese CO₂ Emissions

Abstract:

The text is to establish a combined forecasting model based on the Rough Set (RSCM) ,on the basis of BP Neural Network Model and Support Vector Machine ,in consideration of the Chinese CO2 emission :uncertainty ,imperfection and small sample properties. We predict Chinese CO2 emissions for the same period to verify the effectiveness of combination forecasting model based on rough set, based on the data of the Chinese CO2 emissions from 1990 to 2011. and use this model to predict future Chinese CO2 emissions.

• Periodical: Advanced Materials Research (Volume 773)
• Pages: 831-836
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.773.831
• Online since: September 2013
• Authors: Jian Guo Zhou, Xi Gang Zhang
• Keywords: BP Neural Network (BPNN), Combined Forecasting Model, Rough Set (RS), Support Vector Machine (SVM)

References

[1] Wang Jiang , Jin Zhanming. Evaluation of intangible assets combination forecast method based on rough set theory [J]. Mathematical statistics on management , 2005, 02: 45 -49 +83.

[2] Xiao Zhi, Zheng Daxia, Grain Yield Forecasting combination forecasting method based on rough set [J]. Statistics and Decision , 2005, 08: 130-132.

[3] Tian Guangli, Yuan Hongwei, Niu Dening. Study of short-term traffic flow prediction based on rough set theory [J]. Road Traffic and Safety , 2010, 02: 23 -26 +30.

[4] Zhong Bo, Xiao Zhi, Zhou Jiaqi Weights based on rough set theory in combination forecasting method for determining [J]. For -130, Chongqing University of Science and Technology (Natural Science) , 2002, 07: 127.

[5] Chen Hongtao, Zhou Dequn. Performance assessment indexes based on rough set theory about Jane [J] computer the Applied Research , 2007, 12: 109-111.

[6] Cha Donglan, Zhou Dequn. Differences in the areas of energy efficiency and carbon dioxide emissions - based on Kaya factor in decomposition [J]. The systems engineering , 2007, 11: 65-71.

[7] Bo Li, Yang Cao. An Improved Comprehensive Evaluation Model of Software Dependability based on Rough Set Theory [J]. Journal of Software, 2009.

DOI: 10.4304/jsw.4.10.1152-1159

[8] Ravi shankar N., Ravi Kumar B., Srikanth T. Rough Set Model using Lattice theory [J]. International Journal of Machine Intelligence, 2010.

[9] Jiang, Hua, Ruan Junhu. Applying on Rough Set Theory to Evaluate Network Marketing Performance of Chinese Agricultural Products [J] Computer journal, 2010, 58.

DOI: 10.4304/jcp.5.8.1264-1272

[10] Li, Bo, Cao, Yang An Improved, Comprehensive Evaluation Model of Software Dependability based on Rough Set Theory [J] software journals, 2009, 410.

DOI: 10.4304/jsw.4.10.1152-1159

[11] Lech Polkowski. Rough Mereology: A Rough Set Paradigm for Unifying Rough Set Theory and Fuzzy Set Theory [J]. Information Science foundation, 2003, 541.

DOI: 10.1007/3-540-39205-x_9

[12] Yanbing Liu, Shixin Sun, Menghao Wang, Hong Tang. Routing Attribute Data Mining Based on Rough Set Theory [J]. International Journal of Data Warehousing and Mining (IJDWM), 2006, 23.

DOI: 10.4018/jdwm.2006070103

[13] Zhang Limin, Liu Feng, Liu Kai. A support vector machine classification algorithm based on rough set theory [J]. The China Electronics Research Institute of , 2012, 03: 241-245.

[14] Zhao Yi, Zhou Jianguo, Liang Huaitao. Forecast based on gray combination of support vector machine model of thermal power NO_x emissions [J]. Environmental Sciences , 2011, 05: 489-496.

[15] Li Yuanyuan. Based on Rough Set Index System and Comprehensive Evaluation Method Research [D]. Wuhan University of Technology, (2009).

[16] Zhang Guojun. Based on rough set relative attribute reduction algorithm and decision-making method research [D]. Huazhong University of Science and Technology, (2010).

[17] Wang Guoyin, Yaoyiyu, Yuhong. Rough Set Theory and Application Research [J]. The computer of , 2009, 07: 1229-1246.