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

This paper develops a spatial analysis approach, which incorporates three components and a carbon dioxide (CO2) emission factor, has been developed to evaluate the multi-state weighted behaviours with CO2 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 Theta 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 CO2 emission under uncertainty. A simulation for the city of Chongqing in China has been conducted and the results show that the proposed Theta 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. (C) 2012 Elsevier B. V. All rights reserved.