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 Θ 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 Θ 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.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Mendel genetic algorithm (Mendel-GA). ► Multi-state weighted behaviours modelling. ► CO2 emission estimation via GDP data. ► The functional region affecting index.