Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: The China case

Huang, Wencheng; Shen, Bin; Sun, Yu; Wang, Yang; Antwi, Eric Ofosu

doi:10.1016/j.tra.2018.03.025

Cited by 105 publications

(61 citation statements)

References 41 publications

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“…For example, the weight of various indicators is given in advance, which means the evaluation result is based on subjective judgment to some extent [57,58]. In order to make up for this imperfection of the TOPSIS evaluation method and more objectively evaluate the air quality of the PRD cities based on the six major air pollutants, this paper has integrated the entropy value into the TOPSIS evaluation method based on research trends in recent years to scientifically calculate the weight of each indicator and achieve more objective evaluation results [59][60][61]. The specific calculation steps are as follows:…”

Section: Methodsmentioning

confidence: 99%

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Gao

Yang

et al. 2019

Atmosphere

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The evaluation of China’s air pollution and the effectiveness of its governance policies is currently a topic of general concern in the academic community. We have improved the traditional evaluation method to construct a comprehensive air quality assessment model based on China’s major air pollutants. Using the daily air pollutant data of 2015–2018, we calculated and analyzed the monthly air quality of nine cities in the Pearl River Delta of China, and conducted a comparative study on the effect of the air pollution control policies of the cities in the Pearl River Delta. We found that the air quality control policies in those nine cities were not consistent. Specifically, the pollution control policies of Guangzhou and Foshan have achieved more than 20% improvement. The pollution control policies of Dongguan and Zhaoqing have also achieved more than 10% improvement. However, due to the relative lag of the formulation and implementation of air pollution control policies, the air quality of Jiangmen, Zhuhai and Zhongshan has declined. Based on the analysis of the air quality assessment results and the effects of governance policies in each city during the study period, we propose suggestions for further improvement of the effectiveness of air pollution control policies in the region.

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Section: Methodsmentioning

confidence: 99%

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Gao

Yang

et al. 2019

Atmosphere

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“…The entropy weight method has been widely used in such fields as social economy. The basic principle is to determine the objective weight based on the magnitude of the indicator variability (Huang et al, 2018). Meanwhile, the TOPSIS multi-criteria evaluation model ranks the limited number of existing objects in terms of their relative advantages and disadvantages based on their closeness to the ideal objectives (Mavi et al, 2016).…”

Section: Basic Framework Of Modelmentioning

confidence: 99%

Identifying factors influencing total-loss marine accidents in the world: Analysis and evaluation based on ship types and sea regions

et al. 2019

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The world shipping industry is risky involving high uncertainties, and maritime safety has a direct bearing on human life, property and health of the marine environment. Therefore, safety has always been the focus of maritime transportation. Total-loss marine accidents present the most serious accident type in terms of economic cost. It is therefore crucial for decision-making and guidance on rational safety resource allocation through the analysis and evaluation of the influential factors of total-loss marine accidents. Its novelty lies in the pioneering analysis of all the factors solely influencing total-loss accidents in the whole world region, hence aid the development of a big database on total-loss marine accidents for rational safety policy making. This paper involves 16 ship types and 13 main navigation sea regions and analyses the data on the total-loss marine accidents that occurred in the world from 1998 to 2018. As a result, 11 main influential factors are selected and evaluated by an improved entropy weight-TOPSIS model. The results show that, in the both models with respect to ship type and sea region, the main influential factors are foundering, stranding and fires/explosions. Based on such findings, this paper proposes a series of countermeasures with respect to different factors respectively, which will aid the relevant maritime safety authorities such as the International Maritime Organization and ship owners/operations to take effective risk control actions to avoid/reduce the occurrence of total-loss marine accidents in future.

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“…When the credits are accumulated to a certain amount, rewards (e.g., bike-sharing-use discount) can be offered to promote the reduction of carbon emissions. Such an approach is of paramount importance, especially in an era with increasing awareness of environmental protection all over the world [31,50].…”

Section: Discussionmentioning

confidence: 99%

Last-Mile Travel Mode Choice: Data-Mining Hybrid with Multiple Attribute Decision Making

et al. 2019

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Transit offers stop-to-stop services rather than door-to-door services. The trip from a transit hub to the final destination is often entitled as the “last-mile” trip. This study innovatively proposes a hybrid approach by combining the data mining technique and multiple attribute decision making to identify the optimal travel mode for last-mile, in which the data mining technique is applied in order to objectively determine the weights. Four last-mile travel modes, including walking, bike-sharing, community bus, and on-demand ride-sharing service, are ranked based upon three evaluation criteria: travel time, monetary cost, and environmental performance. The selection of last-mile trip modes in Chengdu, China, is taken as a typical case example, to demonstrate the application of the proposed approach. Results show that the optimal travel mode highly varies by the distance of the “last-mile” and that bike-sharing serves as the optimal travel mode if the last-mile distance is no more than 3 km, whilst the community bus becomes the optimal mode if the distance equals 4 and 5 km. It is expected that this study offers an evidence-based approach to help select the reasonable last-mile travel mode and provides insights into developing a sustainable urban transport system.

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Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: The China case

Cited by 105 publications

References 41 publications

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Analysis of the Air Quality and the Effect of Governance Policies in China’s Pearl River Delta, 2015–2018

Identifying factors influencing total-loss marine accidents in the world: Analysis and evaluation based on ship types and sea regions

Last-Mile Travel Mode Choice: Data-Mining Hybrid with Multiple Attribute Decision Making

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