Search results

1 – 10 of 38
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 29 April 2021

Huan Wang, Yuhong Wang and Dongdong Wu

To predict the passenger volume reasonably and accurately, this paper fills the gap in the research of quarterly data forecast of railway passenger volume. The research results…

391

Abstract

Purpose

To predict the passenger volume reasonably and accurately, this paper fills the gap in the research of quarterly data forecast of railway passenger volume. The research results can also provide references for railway departments to plan railway operation lines reasonably and efficiently.

Design/methodology/approach

This paper intends to establish a seasonal cycle first order univariate grey model (GM(1,1) model) combing with a seasonal index. GM (1,1) is termed as the trend equation to fit the railway passenger volume in China from 2014 to 2018. The railway passenger volume in 2019 is used as the experimental data to verify the forecasting effect of the proposed model. The forecasting results of the seasonal cycle GM (1,1) model are compared with the traditional GM (1,1) model, seasonal grey model (SGM(1,1)), Seasonal Autoregressive Integrated Moving Average (SARIMA) model, moving average method and exponential smoothing method. Finally, the authors forecast the railway passenger volume from 2020 to 2022.

Findings

The quarterly data of national railway passenger volume have a clear tendency of cyclical fluctuations and show an annual growth trend. According to the comparison of the modeling results, the authors know that the seasonal cycle GM (1,1) model has the best prediction effect with the mean absolute percentage error of 1.32%. It is much better than the other models, reflecting the feasibility of the proposed model.

Originality/value

As the previous grey prediction model could not solve the series prediction problem with seasonal fluctuation, and there are few research studies on quarterly railway passenger volume forecasting, GM (1,1) model is taken as the trend equation and combined with the seasonal index to construct a combination forecasting model for accurate forecasting results in this study. Besides, considering the impact of the epidemic on passenger volume, the authors introduce a disturbance factor to deal with the forecasting results in 2020, making the modeling results more scientific, practical and referential.

Details

Grey Systems: Theory and Application, vol. 12 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Access Restricted. View access options
Article
Publication date: 30 May 2024

Youyang Ren, Yuhong Wang, Lin Xia, Wei Liu and Ran Tao

Forecasting outpatient volume during a significant security crisis can provide reasonable decision-making references for hospital managers to prevent sudden outbreaks and dispatch…

67

Abstract

Purpose

Forecasting outpatient volume during a significant security crisis can provide reasonable decision-making references for hospital managers to prevent sudden outbreaks and dispatch medical resources on time. Based on the background of standard hospital operation and Coronavirus disease (COVID-19) periods, this paper constructs a hybrid grey model to forecast the outpatient volume to provide foresight decision support for hospital decision-makers.

Design/methodology/approach

This paper proposes an improved hybrid grey model for two stages. In the non-COVID-19 stage, the Aquila Optimizer (AO) is selected to optimize the modeling parameters. Fourier correction is applied to revise the stochastic disturbance. In the COVID-19 stage, this model adds the COVID-19 impact factor to improve the grey model forecasting results based on the dummy variables. The cycle of the dummy variables modifies the COVID-19 factor.

Findings

This paper tests the hybrid grey model on a large Chinese hospital in Jiangsu. The fitting MAPE is 2.48%, and the RMSE is 16463.69 in the training group. The test MAPE is 1.91%, and the RMSE is 9354.93 in the test group. The results of both groups are better than those of the comparative models.

Originality/value

The two-stage hybrid grey model can solve traditional hospitals' seasonal outpatient volume forecasting and provide future policy formulation references for sudden large-scale epidemics.

Details

Grey Systems: Theory and Application, vol. 14 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

Access Restricted. View access options
Article
Publication date: 11 October 2023

Yuhong Wang and Qi Si

This study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.

126

Abstract

Purpose

This study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.

Design/methodology/approach

In this paper, the Interaction Effect Grey Power Model of N Variables (IEGPM(1,N)) is developed, and the Dragonfly algorithm (DA) is used to select the best power index for the model. Specific model construction methods and rigorous mathematical proofs are given. In order to verify the applicability and validity, this paper compares the model with the traditional grey model and simulates the carbon emission intensity of China from 2014 to 2021. In addition, the new model is used to predict the carbon emission intensity of China from 2022 to 2025, which can provide a reference for the 14th Five-Year Plan to develop a scientific emission reduction path.

Findings

The results show that if the Chinese government does not take effective policy measures in the future, carbon emission intensity will not achieve the set goals. The IEGPM(1,N) model also provides reliable results and works well in simulation and prediction.

Originality/value

The paper considers the nonlinear and interactive effect of input variables in the system's behavior and proposes an improved grey multivariable model, which fills the gap in previous studies.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Access Restricted. View access options
Article
Publication date: 20 February 2023

Yuhong Wang, Xiaoqi Sheng and Yudie Xie

This study aims to establish a centralized decision-making game model and manufacturer-led Stackelberg game model based on factors of risk aversion of supply chain members and…

390

Abstract

Purpose

This study aims to establish a centralized decision-making game model and manufacturer-led Stackelberg game model based on factors of risk aversion of supply chain members and product greenness. The research aims to study whether the introduction of the “cost + risk sharing” contract affects coordination of this type of green supply by calculating the optimal decision of each mode.

Design/methodology/approach

This research designs a supply chain model under centralized and decentralized decision-making. This model uses the Stackelberg game to calculate the optimal decision under decentralized decision-making to evaluate the effect of a green supply chain and then analyze the “cost + risk sharing” contract and the degree of coordination of the supply chain. A sensitivity analysis is conducted on the centralized mode for the impact of variables on the supply chain.

Findings

This research finds a double marginalization effect in decentralized decision-making, and the risk aversion coefficient plays a decisive role in the utility of supply chain members. The specific range of risk- and cost-sharing factors allows supply chain members to achieve Pareto improvements and provides decision-making based on the corresponding management strategies according to each other’s risk preference degree.

Research limitations/implications

The influence of each variable on the green supply chain in the centralized mode is studied by MATLAB numerical simulation. It provides reference for green supply chain members to formulate corresponding management strategies according to each other's risk preference degree.

Originality/value

This research innovatively considers manufacturers and retailers to explore the market demand for product greenness. It introduces a novel “cost + risk sharing” contract to coordinate the green supply chain.

Details

Chinese Management Studies, vol. 18 no. 1
Type: Research Article
ISSN: 1750-614X

Keywords

Access Restricted. View access options
Article
Publication date: 6 January 2022

Wuyong Qian, Hao Zhang, Aodi Sui and Yuhong Wang

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for…

270

Abstract

Purpose

The purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.

Design/methodology/approach

Due to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.

Findings

China's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.

Originality/value

The paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.

Details

Grey Systems: Theory and Application, vol. 12 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Access Restricted. View access options
Article
Publication date: 13 December 2022

Zhenhua Luo, Juntao Guo, Jianqiang Han and Yuhong Wang

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in…

666

Abstract

Purpose

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

Design/methodology/approach

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

Findings

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

Originality/value

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Details

Engineering, Construction and Architectural Management, vol. 31 no. 4
Type: Research Article
ISSN: 0969-9988

Keywords

Access Restricted. View access options
Article
Publication date: 15 April 2022

Tianmeng Fan and Yuhong Wang

The purpose of this study is to build a consensus model of social network group decision-making (SNGDM) based on improved PageRank algorithm. By objectively and fairly measuring…

147

Abstract

Purpose

The purpose of this study is to build a consensus model of social network group decision-making (SNGDM) based on improved PageRank algorithm. By objectively and fairly measuring the evaluation ability of participants in the decision-making process, the authors can improve the fairness and authenticity of the weight solution of decision-makers (DM) in the decision-making process. This ensures the reliability of the final group consensus results.

Design/methodology/approach

This study mainly includes six parts: preference expression, calculation of DM's weight, preference aggregation, consensus measurement, opinion adjustment and alternative selection. First, Pythagorean fuzzy expression is introduced to express the preference of DMs, which expands the scope of preference expression of DMs. Second, based on the social network structure among DMs, the process of “mutual judgment” among DMs is increased to measure the evaluation ability of DMs. On this basis, the PageRank algorithm is improved to calculate the weight of DMs. This makes the process of reaching consensus more objective and fair. Third, in order to minimize the evaluation difference between groups and individuals, a preference aggregation model based on plant growth simulation algorithm (PGSA) is proposed to aggregate group preferences. Fourth, the consensus index of DMs is calculated from three levels to judge whether the consensus degree reaches the preset value. Fifth, considering the interaction of DMs in the social network, the evaluation value to achieve the required consensus degree is adjusted according to the DeGroot model to obtain the overall consensus. Finally, taking the group preference as the reference, the ranking of alternatives is determined by using the Pythagorean fuzzy score function.

Findings

This paper proposes a consensus model of SNGDM based on improved PageRank algorithm to aggregate expert preference information. A numerical case of product evaluation is introduced, and the feasibility and effectiveness of the model are explained through sensitivity analysis and comparative analysis. The results show that this method can solve the problem of reaching consensus in SNGDM.

Originality/value

Different DMs may have different judgment criteria for the same decision-making problem, and the angle and depth of considering the problem will also be different. By increasing the process of mutual evaluation of DMs, the evaluation ability of each DM is judged only from the decision-making problem itself. In this way, the evaluation opinions recognized by most DMs will form the mainstream of opinions, and the influence of corresponding DMs will increase. Therefore, in order to improve the fairness and reliability of the consensus process, this study measures the real evaluation ability of DMs by increasing the “mutual judgment” process. On this basis, the defect of equal treatment of PageRank algorithm in calculating the weight of DMs is improved. This ensures the authenticity and objectivity of the weight of DMs. That is to improve the effectiveness of the whole evaluation mechanism. This method considers both the influence of DMs in the social network and their own evaluation level. The weight of DMs is calculated from two aspects: sociality and professionalism. It provides a new method and perspective for the calculation of DM’s weight in SNGDM.

Details

Kybernetes, vol. 52 no. 9
Type: Research Article
ISSN: 0368-492X

Keywords

Access Restricted. View access options
Article
Publication date: 27 January 2012

Yuhong Wang, Jiangrong Tang and Wenbin Cao

The purpose of this paper is to make an evaluation and early warning prediction using grey prediction models and the index of process ability.

924

Abstract

Purpose

The purpose of this paper is to make an evaluation and early warning prediction using grey prediction models and the index of process ability.

Design/methodology/approach

An early warning prediction for food security risk is proposed in this paper. A quality index is constructed and an improved grey prediction model is also presented. The quality index model is applied to measure the level of food quality; then the grey prediction model is applied to predict the trend of quality index for food in the future. A comparison between the predicted trends and standard limit proposed by experts is made to judge the food security risk.

Findings

The results in this paper indicate that more attention should be paid to the food security situation and steps should also should be taken to prevent harm to people's health from food.

Practical implications

The method presented in the paper could be used to make predictions for those systems which have the characteristic of small sample and poor information. The combination of grey prediction model and process ability index could also be applied to evaluation and early warning for those systems.

Originality/value

Food quality index is constructed for evaluating food security and an improved grey prediction model is also presented in this paper. The combination of these two models could be applied to make evaluation and warning prediction for food security risk with poor information.

Details

Grey Systems: Theory and Application, vol. 2 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Access Restricted. View access options
Article
Publication date: 4 February 2014

Ying Huang, Sheng Han, Sizhou Liu, Yuhong Wang and Jiusheng Li

To develop a potential substitute for conventional lubricant additive and improve the oil-solubility of nanoparticles, calcium borate nanoparticles modified by an eco-friendly or…

327

Abstract

Purpose

To develop a potential substitute for conventional lubricant additive and improve the oil-solubility of nanoparticles, calcium borate nanoparticles modified by an eco-friendly or “green” modifier lauric acid (CBLA) were prepared. The paper aims to discuss these issues.

Design/methodology/approach

The microstructures of the as-obtained samples were characterized by X-ray power diffraction (XRD) transmission electron microscope (TEM) and infrared spectra (IR). The contact angle was also measured. Tribological properties of CBLA used as additive in base oil were evaluated with a four-ball tribotester and compared with a commercial additive. The worn surface was investigated by polarized microscope (PM) and X-ray photoelectron spectroscopy (XPS).

Findings

The results indicate that the average size is in the range of 50-100 nm and the surface of calcium borate was altered from hydrophilicity to hydrophobicity. At the same time, the nanoparticles can be dispersed well in the base oil. Tribological results show that CBLA have good antiwear property and friction-reducing property in base oil, and it can be found that during the sliding process, a continuous wear resistance film was formed which containing depositions and the tribochemical reaction products such as B2O3, FeB, Fe2O3 and CaO.

Originality/value

An eco-friendly or “green” modifier lauric acid could change the surface of calcium borate from hydrophilicity to hydrophobicity, and calcium borate modified by lauric acid has good tribological properties in lubricating oil.

Details

Industrial Lubrication and Tribology, vol. 66 no. 1
Type: Research Article
ISSN: 0036-8792

Keywords

Available. Content available
Article
Publication date: 17 August 2012

415

Abstract

Details

Grey Systems: Theory and Application, vol. 2 no. 2
Type: Research Article
ISSN: 2043-9377

1 – 10 of 38
Per page
102050