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

Yi Chen; Xinyu  Wang; Zhijie  Sha; Shaomin  Wu

doi:10.1016/j.asoc.2012.04.014

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

Yi Chen, Xinyu Wang, Zhijie Sha, Shaomin Wu

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	2631-2637
Number of pages	7
Journal	Applied Soft Computing
Volume	12
Issue number	8
DOIs	https://doi.org/10.1016/j.asoc.2012.04.014
Publication status	Published - Aug 2012

Keywords

spatial analysis
carbon dioxide emission
mendel genetic algorithm
functional region
China
uncertainity

Documents and Links

10.1016/j.asoc.2012.04.014

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

abstract = "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. ",

keywords = "spatial analysis, carbon dioxide emission , mendel genetic algorithm, functional region, China, uncertainity",

author = "Yi Chen and Xinyu Wang and Zhijie Sha and Shaomin Wu",

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T1 - Uncertainty analysis for multi-state weighted behaviours of rural area with carbon dioxide emission estimation

AU - Chen, Yi

AU - Wang, Xinyu

AU - Sha, Zhijie

AU - Wu, Shaomin

N1 - Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.asoc.2012.04.014.

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N2 - 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.

AB - 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.

KW - spatial analysis

KW - carbon dioxide emission

KW - mendel genetic algorithm

KW - functional region

KW - China

KW - uncertainity

U2 - 10.1016/j.asoc.2012.04.014

DO - 10.1016/j.asoc.2012.04.014

M3 - Article

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SP - 2631

EP - 2637

JO - Applied Soft Computing

JF - Applied Soft Computing

SN - 1568-4946

IS - 8

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