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A platform for research: civil engineering, architecture and urbanism
Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods
City sustainability is an important issue in the urbanization process. In this paper, the sustainability of 14 cities in Liaoning province in China is evaluated and predicted. The process of evaluating city sustainability is viewed as a multi-criteria decision-making problem. A simple additive weighting method is used for aggregating the normalized sustainability criteria data, built based on the three-pillar model and the associated weights. The results indicate that although the sustainability of the cities in Liaoning province is not perfect, the cities show better development momentum. For example, only two cities’ (Shenyang and Dalian) average performance scores in 2010–2016 were over 0.5, but all the cities’ sustainability improved in 2016 compared to 2010. We develop a stochastic simulation procedure used for predicting a city’s sustainability in future years. Many prediction results were obtained, including the maximum, minimum, and average performance scores of the cities, the pairwise priority matrix representing the ratio of one city outperforming another, and the ranking of cities’ sustainability with probabilities. The prediction results indicate various degrees of increase for almost all the cities’ sustainability in the future, which is consistent with the judgment of better development momentum determined from the evaluation results. Moreover, the cities of Dandong, Panjin may exceed Shenyang, Dalian, and rank in the top among all the cities in future years.
Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods
City sustainability is an important issue in the urbanization process. In this paper, the sustainability of 14 cities in Liaoning province in China is evaluated and predicted. The process of evaluating city sustainability is viewed as a multi-criteria decision-making problem. A simple additive weighting method is used for aggregating the normalized sustainability criteria data, built based on the three-pillar model and the associated weights. The results indicate that although the sustainability of the cities in Liaoning province is not perfect, the cities show better development momentum. For example, only two cities’ (Shenyang and Dalian) average performance scores in 2010–2016 were over 0.5, but all the cities’ sustainability improved in 2016 compared to 2010. We develop a stochastic simulation procedure used for predicting a city’s sustainability in future years. Many prediction results were obtained, including the maximum, minimum, and average performance scores of the cities, the pairwise priority matrix representing the ratio of one city outperforming another, and the ranking of cities’ sustainability with probabilities. The prediction results indicate various degrees of increase for almost all the cities’ sustainability in the future, which is consistent with the judgment of better development momentum determined from the evaluation results. Moreover, the cities of Dandong, Panjin may exceed Shenyang, Dalian, and rank in the top among all the cities in future years.
Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods
Pingtao Yi (author) / Weiwei Li (author) / Lingyu Li (author)
2018
Article (Journal)
Electronic Resource
Unknown
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