Uncertainty analysis for multi-state weighted behaviours of rural area with carbon dioxide emission estimation

Authors:
Yi Chen;Xinyu Wang;Zhijie Sha;Shaomin Wu
Affiliations:
School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China and Department of Mechanical Engineering, University of Glasgow, Glasgow G12 8QQ ...;School of Management, China University of Mining and Technology, Xuzhou 221116, China;Department of Civil and Environmental Engineering, Imperial College, London SW7 2AZ, UK;School of Applied Sciences, Cranfield University, Bedfordshire MK43 0AL, UK
Venue:
Applied Soft Computing
Year:
2012

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Abstract

This paper develops a spatial analysis approach, which incorporates three components and a carbon dioxide (CO"2) emission factor, has been developed to evaluate the multi-state weighted behaviours with CO"2 emission uncertainty of the rural areas at an administrative district level. A Mendel genetic algorithm (Mendel-GA) is applied to the spatial analysis problem, where the Mendel genetic operator implies the random assignment of alleles from parents to their offspring by using the Mendel's principles. A functional region affecting index @Q is developed as a fitness function for the Mendel-GA driven evaluation, in which a gross domestic product (GDP) data based method is utilised to estimate the CO"2 emission under uncertainty. A simulation for the city of Chongqing in China has been conducted and the results show that the proposed @Q modelling method can work valuably for the spatial analysis of the functional regions and can be taken as a technical tool for the policy makers at the rural area level.