Table of Content

01 June 2023, Volume 35 Issue 2

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AGMC Model for Forecasting Carbon Dioxide Emission in Northwestern China

Kedong Yin, Haolei Gu

2023, 35(2):  1-13. 

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With economic and social development rapidly, carbon dioxide emission soared in the northwestern region. The importance of adopting emission reduction strategies cannot be overemphasized. Therefore, it is essential to accurately forecast carbon dioxide emission in northwestern China. The study used Lasso parameter estimation to select influential carbon dioxide emission features. FGM(1,1) model was used to forecast features trend. The adjacent accumulation grey multivariate convolution model (AGMC) model forecasts carbon dioxide emission trend. The future two years forecast result shows that Shaanxi province’s carbon dioxide emission will show a fluctuating trend. Qinghai autonomous regions will show a decreasing trend. Other regions will be in upward trend. The study suggests the central government should pay attention to the carbon emission problem in the northwestern region. Government increases science and technology investment and pays attention to urbanization spatial pattern rational layout. 

The Impact of Claim Management on Selecting Contractors Using the Grey Ordinal Priority Approach (OPA-G)

Hamid Asnaashari, Abbas Sheikh Aboumasoudi, Mohammad Reza Mozaffari, Mohammad Reza Feylizadeh

2023, 35(2):  14-40. 

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This study aimed to explore the causes and origins of claims in the oil and gas industry. It also sought to find solutions, reduce or eliminate claims, and use them to select efficient contractors. In this paper, one of the new multi-attribute decision-making methods, called the grey ordinal priority approach, was used to rank criteria and alternatives. For dealing with uncertainty, grey systems theory was also applied. Finally, some criteria were proposed to identify and select more efficient contractors. The Grey systems theory can reduce the incidence of claims and increase productivity by ranking claim solutions to reduce costs and execution time, increase quality, and use these solutions in selecting contractors. The variations between the “grey ranks” and the “targeted changes observed” showed that an increase in distance between the ranks increases the effect of the top ranks. Besides, the increase of the grey range of the total weights from [0.8, 1.2] to [0.5, 1.5] made the scores fluctuations regular, and the rankings were shifted to weaker ranks with the closest competition. The contributions of this study are as follows: (1) Unlike previous research that focused on prioritizing the causes of claims, this study tried to identify and rank solutions to reduce the occurrence of claims; (2) The recognized solutions were presented as criteria for selecting more efficient contractors; (3) grey ordinal priority approach method has been used to compare and rank the proposed solutions to increase productivity, considering cost, time, and quality criteria; and (4) This method was first used in project claim management. This method showed that the criterion of “Employing a technical team with experienced and educated members” has the first, and the criterion of “Ensuring the contractor’s effective service records” has the second rank.

A Novel Grey Incidence Analysis Model Based on Gamma Probability Density Function and Its Application

Yu Feng, Yaoguo Dang, Deling Yang, Junjie Wang, Huimin Zhou

2023, 35(2):  41-54. 

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Aiming at the problem that existing grey incidence analysis methods cannot effectively characterize the difference of development trends between sequences in line with the normativity axiom, a novel grey incidence analysis model based on the Gamma probability density function (GIAMG) is proposed. First, the projection factor is defined based on the geometric projection between sequences. Then, the grey incidence coefficient (GIC) is designed by combining the projection factor and the Gamma probability density function. According to the difference in development trends in different periods, the degree of grey incidence is constructed by summing up the GICs with variable weight. Finally, the GIAMG is used to identify the main air pollutants for respiratory diseases in Tianjin, China. Experimental results show that the proposed model is superior in the reliability and effectiveness of the related order over four traditional incidence models. 

Forecasting Productive Inventory by Using Graphical Evaluation and Review Technique with Grey Number Representation

Jing Zeng

2023, 35(2):  55-67. 

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Quantitative forecasting of the inventory for key products can help to reduce the amount of inventory obsolescence and prevent production delays due to raw material stock-outs. Predicting productive inventory is beneficial to promote the sustainability of production management. In this work, a prediction model is constructed that predicts the pass rate of products and the processing path of unqualified products and simultaneously calculates the quantity, time, and probability of each path. Using the Graphical Evaluation and Review Technique (GERT), the manufacturing process of a square tube can be transformed into a stochastic network. Then, grey parameters are introduced into the GERT network to solve uncertainty in manufacturing. Finally, a numerical example is given to obtain a productive inventory prediction for beam square tubes using grey GERT(G-GERT). The main contribution of this work is the integration of inventory quantity, time, and probability. These three results can be predicted simultaneously, and the algorithm can be extended to any product production network.

Identifying Influential Nodes in Complex Networks Based on Multi-Information Fused Degree of Grey Incidence

Jinhua Zhang, Qishan Zhang, Ling Wu, Lijuan Weng, Xiaojian Yuan, Jinxin Zhang

2023, 35(2):  68-86. 

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This paper proposes a new synthetic measure of node centrality, namely, multi-information fused degree of grey incidence centrality (MIFDC), which is used to evaluate the importance of nodes and identify influential nodes in complex networks. It is the first time that the grey incidence analysis (GIA) and the D-S evidence theory are combined to identify influential nodes in complex networks in the MIFDC method. The proposed MIFDC measure comprehensively considers the information of multiple centrality measures and can correct the subjective bias problem in the selection process of the grey incidence operator. To verify the performance of the proposed method, the MIFDC method is applied to identify influential nodes in two real networks, the Advanced Research Project Agency (ARPA) network, and the terrorist relationship network. The application results show that the MIFDC method can effectively identify the influential nodes of the network.  

Forecasting the Evolution of Public Opinion Using a Novel Improved Grey Model During Emergencies

Hongchan Li, Yu Ma, Haodong Zhu

2023, 35(2):  87-104. 

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Public opinion is an aggregate of people’s views, attitudes, and emotions about events that can spread through the Internet to generate online public opinion. Studying the evolution of online public opinion during emergencies can help relevant departments to take targeted measures to respond in advance. Tweets and Weibo texts with negative emotions are essential factors affecting the evolution of online public opinion. To this end, this paper proposes a novel improved grey model, SISGM(1,1), that optimizes initial conditions and background values for predicting the number of negative Weibo texts generated during emergencies. The model is improved as follows: First, the background value is reconstructed by the Simpson rule to achieve the effect of smoothing the data sequence. Second, the ISRU activation function is used to modify the initial condition, which can better reveal the characteristics of data growth and improve the model’s adaptability. Then, the modified background value is combined with the optimized initial condition to realize the double optimization. Finally, the PSO algorithm is used to calculate the introduced parameters to improve the prediction accuracy further. Additionally, the model is compared with five competing models to predict the evolution of online public opinion during emergencies. The experimental results demonstrate that the proposed model has apparent advantages compared to the other five competing models.  

A Grey Three-Way Decision Approach and Its Application

Xuege Guo, Yong Liu, Huanhuan Zhao, Hanru Zhang, Gang Zhao, Zhiying Han

2023, 35(2):  105-129. 

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The three-way decision offers new perspectives for solving uncertain decision problems, especially categorical decision-making. However, in reality, the preference information of the decision object may be vague and uncertain. To address this issue, we construct a grey relation analysis based three-way decision model in a grey system environment. First, based on an improved grey correlation similarity measure, we investigate how the conditional probabilities of decision events are constructed. Subsequently, according to the information entropy, we established the objective optimization model and calculated the optimal weight of each index. Considering the delay cost and the uncertainty of the loss function, the grey relative loss function matrix is constructed based on the uncertain information of decision objects. Based on this, we establish the optimal thresholds method with the relative loss function and devise the decision rules. Using the established decision rules, we can obtain the classification results of all decision objects. Finally, the proposed model is used to deal with the users’ classification problems in the movie recommendation system, which demonstrates the validity and feasibility of the model.  

Grey Clustering Analysis of Provincial Scientific and Technological Innovation Capability Mainland

Yuying Yang, Yuxuan Huang, Yichen Liu, Bin Liu

2023, 35(2):  130-148. 

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The scientific and technological innovation capabilities of different provinces and cities in China are quite different. Comprehensive evaluation and analysis of provincial scientific and technological innovation capabilities are conducive to a more comprehensive and targeted understanding of different regional differences and put forward more effective policy recommendations for balanced and coordinated regional development. Firstly, this paper constructs the evaluation index system of scientific and technological innovation ability from four aspects: innovation input, innovation output, innovation carrier, and innovation environment; Secondly, using the method of combining subjectivity and objectivity, the indicators are weighted to reflect the importance of different indicators on scientific and technological innovation capability; Finally, the paper uses the grey weight clustering method to analyze the scientific and technological innovation capacity of 31 provinces and cities mainland from 2010 to 2020. The study found that there are significant geographical differences in China's scientific and technological innovation capabilities. The provinces and cities with strong scientific and technological innovation capabilities are mainly Beijing, Shanghai, Jiangsu, Zhejiang, and Guangzhou, which can enhance the scientific and technological innovation capabilities of surrounding provinces and cities through regional synergy.  

Forecasting China’s Hydroelectric Power Generation Under the New Era Based on Grey Combination Model

Shuliang Li, Nannan Song, Ke Gong, Bo Zeng, Yingjie Yang

2023, 35(2):  149-166. 

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It's necessary to forecast hydroelectric power generation under the background of carbon peak. Firstly, based on the three-parameter whitening grey prediction model, the order of the accumulating-fractional-order in the real field and the coefficients of the background value are combined and optimized to establish a two-parameter optimized three-parameter whitening grey prediction model. The model is applied to predict China's hydroelectric power generation, and the comprehensive error is only 1.13%, indicating that the model has good performance. The results show that the carbon peak target can be achieved by 2030. Based on this, relevant countermeasures and suggestions are put forward.  

Study on the Strengthening Buffer Operators Based on Interpolation Functions

Yanfang Wang , Xinyu Qi, Tao Chen, Hui Zhang, Zhengpeng Wu

2023, 35(2):  167-178. 

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Based on the present theories of buffer operators, two kinds of strengthening buffer operators (SBOs) based on interpolation functions are established in this paper. Compared with the ones proposed by Dang, it shows that Dang's SBOs are, in our special case. The properties and the inner connections of different SBOs are discussed, which greatly extend the application range of the SBOs. The main function of the SBOs is to reduce or eliminate the impact of shock disturbed system, to restore the distorted "actual data" to its true state. This is the first time to connect the construction of strengthening buffer operators with interpolation functions, which provides a new routine for constructing SBOs.