An Integrated Algorithm for Low-Carbon City Evaluation Based on Neural Network and Analytic Hierarchy Process

Xiao Yong Tan; Yong Mei Ren

doi:10.4028/www.scientific.net/AMM.631-632.129

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 631-632An Integrated Algorithm for Low-Carbon City...

An Integrated Algorithm for Low-Carbon City Evaluation Based on Neural Network and Analytic Hierarchy Process

Abstract:

The low-carbon city evaluation has great significance to promote the urban construction management and sustainable development of city. In order to establish a suitable low-carbon city evaluation method to measure the performance of low-carbon city planning and construction, based on the index system of low-carbon city evaluation in the Pressure Status Response (PSR) framework, an integrated algorithm for low-carbon city evaluation combining BP neural network with the Analytic Hierarchy Process (AHP) is proposed. Furthermore, the possible ways for optimization have been discussed. The model and algorithm have the following properties: rapid, flexible and feasible.

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Periodical:

Applied Mechanics and Materials (Volumes 631-632)

Pages:

129-132

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.631-632.129

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Online since:

September 2014

Authors:

Xiao Yong Tan*, Yong Mei Ren

Keywords:

Analytic Hierarchy Process (AHP), Evaluation, Low-Carbon City, Neural Network (NN)

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* - Corresponding Author

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