Evaluating Sustainable Liveable City via Multi-MCDM and Hopfield Neural Network

Abstract

Research on liveable cities has received increased attention in recent years because of the complexity and diversity of liveability standards. Evaluating the liveable environment is a multiple criteria decision-making (MCDM) problem, and the results can be used to control environmental pollution and protect human health. However, different evaluation methods can lead to different results; hence, determining how to effectively to obtain the consistent results is a main consideration of this study. The objective of this work is to design an optimal method based on the difference ratio concept. A hopfield neural network is selected to validate the experimental results. Referring to the liveable city rankings established by the Economist Intelligence Unit, thirteen large cities in China are used to illustrate the application of the model, evaluate the liveable urban environment, and demonstrate the effectiveness and feasibility of the proposed model. The results show that Hangzhou is the most liveable city and Beijing has the worst liveable urban environment. Therefore, a common policy should be strengthening environmental governance, with a special focus on the development of low-carbon cities, for which both the local and global environmental impacts could be mitigated.

Büyükşehi̇rleri̇n Yaşanabi̇li̇rli̇k Düzeyleri̇ni̇n Dematel Tabanli Anali̇ti̇k Ağ Süreci̇ (

“…When the results of some related works regarding the livable cities examined, some different criteria about determining of livable cities encountered. In the study of Chen, the evaluation criteria were determined according to environment protection standards of the European Environment Agency and the Technical Criterion for Ecosystem Status Evaluation of PRC and included the average temperature, urban greening coverage, population density, sewage treatment rate, equivalent sound level, days of good air quality, per capita urban road area, and per capita GDP (Chen, 2020). It has been determined that this study is different from the current study in terms of considering environmental criteria more.…”

Strategic Alliance Pattern Evaluation Model for Taiwan’s Machine Tool Industry: A Hierarchical DEMATEL Method

“…ese assessments incorporate elective businesses and geographic regions. Moreover, market expansion distinguishes between elective innovation and extra employments for items, determines any changes within the market conditions, and measures the relative costs for diversifying into the target markets [48,74].…”

“…Identifying causal connections between the impacting variables can give the organization the desired decision-making data [40][41][42][43][44]. Subsequently, we illustrate that the various DEMATEL criteria assessment methods are more effective than the conventional strategy, providing specialists with an important instrument [45][46][47][48][49][50][51].…”

Geodetector-Based Livability Analysis of Potential Resettlement Locations for Villages in Coal Mining Areas on the Loess Plateau of China

“…Basu et al proposed a geographically weighted principal component analysis to evaluate the spatial pattern of urban livability in Raiganj, India [27]. Some studies have implemented machine learning algorithms such as neural networks to obtain or estimate livability [28]. However, these livability evaluation models always contain human settlement factors and geographic factors together.…”