Railway Container Station Reselection Approach and Application: Based on Entropy-Cloud Model

Huang, Wencheng; Shen, Bin; Wang, Lei; Antwi, Eric Ofosu

doi:10.1155/2017/8701081

Cited by 9 publications

(3 citation statements)

References 47 publications

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“…The cloud model proposed by Li and co-workers [ 29 , 30 ] represents a new approach to air quality assessment wherein the uncertainty between qualitative concepts and quantitative values is converted while the fuzziness and randomness are taken into account simultaneously. Cloud models have been applied to the assessment in petrochemical enterprise [ 31 ], railway container station selection [ 32 ], water allocation [ 33 ] and stability analysis [ 34 ]. In this study, a cloud model was used to assess air pollution.…”

Section: Introductionmentioning

confidence: 99%

Assessment of air quality using a cloud model method

Xu¹,

Xu²

2018

R. Soc. open sci.

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To effectively control air pollution, it is necessary to obtain a preliminary assessment of air quality. The purpose of this study was to introduce a cloud model method in air pollution assessment. First, the standard cloud models of air pollution indicators were obtained, and the calculating process of numerical characteristics employed by the standard cloud model was explained. Second, the levels of air pollution indicators were presented based on the qualitative and quantitative analysis of cloud models, which realized the uncertainty conversion between qualitative concepts and their corresponding quantitative values, as well as taking the fuzziness and randomness into account. Air quality assessment results including SO2, NO2, CO, O3, PM10 and PM2.5 were analysed. Third, the cloud model adopted in the assessment process of air quality was validated by grey relational analysis, and the results confirmed the validity of cloud model assessment. Fourth, the air pollution level of the air quality index (AQI) was determined, and the fuzziness and randomness of the assessment results were thoroughly analysed by taking entropy and hyper entropy into consideration. Fifth, seasonal variations in different air pollution indicators were analysed to proffer a series of recommendations for government policy decision-makers and travellers. The cloud model provided a new method for air quality assessment.

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Section: Introductionmentioning

confidence: 99%

Assessment of air quality using a cloud model method

Xu¹,

Xu²

2018

R. Soc. open sci.

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“…Freight and environmental costs can be decreased by increasing the market share of RCT and promoting the shift from road to rail. This entails optimizing container station locations ( 7 ), improving the operational efficiency ( 8 ), and enhancing the service quality ( 9 ), which can help achieve a balance between RCT resources and benefits. Researchers have promoted the development of sea–rail combined transport ( 10 ) by examining the relationship between railway containers and terminals ( 11 ) to accelerate the shift from road to rail.…”

Section: Literature Reviewmentioning

confidence: 99%

Evolution of spatial and temporal patterns of railway container transportation: A case study of China cities

Bai

Kuang²,

Yang³

et al. 2022

Front. Public Health

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The healthy development of railway container transport is an important part of railway freight transport and is key for promoting the green transformation of China's transport and supporting a new pattern of transport development. In this study, railway container handling station (RCHS) data, kernel density analysis, standard deviation ellipse, Herfindahl–Hirschman index (HHI), trend surface analysis (TSA), and R index were applied to examine the evolution characteristics of container transport patterns after the market-oriented reform of China's railway freight transport in 2013. The results are as follows: First, the overall scale growth trend is obvious, and the double-center effect of transport scale on the Bohai Rim region and Chengdu–Chongqing Economic Zone is evident, with the transport center of gravity moving northward. Second, the amount of attraction/occurrence is consistent in spatial distribution, and the aggregation effect of both is similar, essentially exhibiting a tendency of being high in the northwest and low in the southeast. Third, the pattern of “export-oriented in the north and import-oriented in the south” has taken shape; nearly half of cities in China have stable traffic functions, stable traffic supply, and demand relationships, and the change of functions shows that the industrial structure is constantly upgrading. This study elucidates the pattern of railway container transport in cities in China and provides empirical guidance for adjusting the functions of urban freight transport, thereby promoting the healthy development of urban freight transport and optimizing urban transport planning.

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“…They use wireless sensor network technology (one of the IoTs) that can monitor and visualize facilitating big data decision-making on the health and safety of shipping industry workers. In addition, Huang et al (2017) present a new entropy-cloud approach to solve the layout of railway container freight stations. The problems are higher transportation efficiency and less transportation cost.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

The impact of applying knowledge in the technological pillars of Industry 4.0 on supply chain performance

Sawangwong

Chaopaisarn

2021

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PurposeThe purpose of the study is to investigate the impact of technological pillars of Industry 4.0 based on knowledge to adopt the supply chain performance of Thai small and medium-sized enterprises (SMEs) 4.0. In addition, to increase knowledge and understanding of how to apply knowledge in technology 4.0 to improve the efficiency of supply chains and organizations.Design/methodology/approachAn integrated model was developed from applying knowledge in five technological pillars of Industry 4.0 such as Internet of things (IoTs), cloud computing, big data and analytics, additive manufacturing and cyber-security. The bibliometric analysis was used to find the relationship between the technological pillars of Industry 4.0 and the literature review. The survey questionnaires were sent to Thai SME 4.0 (manufacturing aspect). Of these, 240 useable responses were received, resulting in a response rate of 65.84%, after then, the exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM) and validity were used to evaluate the model through IBM SPSS 21 and AMOS 22.FindingsEFA showed the four groups of the technological pillars of Industry 4.0, such as support human, automation, real-time and security. These groups positively impact supply chain performance (increase delivery reliability, increase resource efficiency, decrease costs in the supply chain and reduce delivery time). Another important finding is that supply chain performance positively impacts organizational performance in profitability, return on investment (ROI) and sale growth.Originality/valueThis study is a model development to support the supply chain performance and increase understanding related to applying knowledge in technology 4.0 that remains unclear for SME 4.0.

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Railway Container Station Reselection Approach and Application: Based on Entropy-Cloud Model

Cited by 9 publications

References 47 publications

Assessment of air quality using a cloud model method

Assessment of air quality using a cloud model method

Evolution of spatial and temporal patterns of railway container transportation: A case study of China cities

The impact of applying knowledge in the technological pillars of Industry 4.0 on supply chain performance

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