Matter-element Extension Research Articles

Evaluating High-Quality Development in the Construction Industry via the Matter–Element Extension Method: A Case Study of 11 Cities in Zhejiang, China

China’s construction industry is facing increasing pressure for transformation and upgrading, with high-quality development becoming an essential goal. However, the precise definition and evaluation criteria for high-quality development remain ambiguous. Against this backdrop, this study focuses on 11 cities in Zhejiang province to explore the connotations of high-quality development in the construction industry and establishes an evaluation index system for assessing it. This study employs the entropy weight method and matter–element extension method to evaluate the high-quality development levels of the construction industry across these cities. The empirical results reveal that the development of the construction industry in Zhejiang province is uneven across cities, with significant potential for overall improvement. This study validates the proposed index system and evaluation model while supplementing empirical evidence; it also enriches the literature and provides both theoretical and technical support for advancing the construction industry’s transition toward high-quality development.

Evaluating the Current Situation of River and Lake Shoreline Planning and Utilization Using an Improved Matter-Element Extension Model

Based on the analysis of the influencing factors of the current planning and utilization of river and lake shorelines, an index system of the current planning and utilization of river and lake shorelines is constructed. Based on the triangular fuzzy number method and the improved CRITIC method, the evaluation indicators are weighted and analyzed and then integrated to obtain the combined weight. An improved matter-element extension model was constructed to evaluate the current situation of shoreline planning and utilization in typical regions. At the same time, the TOPSIS evaluation model and the cloud theory evaluation model were compared and analyzed to verify the accuracy of the model. The improved matter-element model accounts for indicator incompatibility and the uncertainty of evaluation boundaries, offering a clearer reflection of the planning and utilization status.

Risk assessment of transmission towers based on variable weight theory and matter-element extension model

Abstract The risk assessment of transmission towers is a critical approach to ensuring the safe and stable operation of power grids. In response to the increasingly frequent and severe impacts of seasonal permafrost on transmission towers in permafrost regions, this paper proposes a novel risk assessment method based on Variable Weight Theory and the Matter-Element Extension Model. By incorporating key influencing factors—such as the number of freeze-thaw cycles, soil moisture content, temperature fluctuations, soil dry density, melting settlement coefficient, and porosity ratio—an indicator system tailored to risk assessment in seasonal permafrost regions is established. Utilizing the Matter-Element Extension Model, this approach applies Variable Weight Theory to integrate both the best-worst method and the entropy weight method for calculating subjective and objective indicator weights. The risk level of the towers is then determined by their proximity to risk thresholds. Finally, a case study involving transmission towers in a specific region of a province in China is presented, where the assessment results are compared with the actual conditions to validate the rationality and effectiveness of the proposed method.

Research on Safety Evaluation of Stadium Reconstruction Construction Based on Combination Weighting Extension Model

As an important carrier of sports services and the main force participating in the “short board” project of urban development, the renovation and upgrading of old stadiums have become an important trend for the sustainable development of venues in the context of urban renewal, consumption upgrading, and national fitness. However, owing to the complexity of the transformation process, the probability of safety accidents continues to increase, posing a serious threat to national property security. In order to reasonably evaluate the safety of the stadium renovation construction process and reduce the incidence of accidents in the renovation project, this study proposed a safety evaluation model for the stadium renovation construction based on the combination weighting extension model. First, according to the 5M1E theory, 27 influencing factors were selected, a safety evaluation index system for stadium reconstruction construction was constructed, and the safety evaluation grade of the index was quantified. Second, based on the analytic hierarchy process (AHP) and improved entropy weight method, the combination weight of the index was determined, and a safety evaluation model was constructed using the matter–element extension theory. Finally, the established evaluation model was applied to the example of stadium renovation, and the construction safety level of the renovation project was obtained. The research results showed that the model has strong operability, and the evaluation results are reasonable and reliable, providing a new concept for the safety control of stadium reconstruction construction.

A comprehensive framework for evaluating and predicting investment risks in renewable energy projects: a case study of Maynak hydropower station

ABSTRACT This study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. This framework aims to reduce the uncertainties inherent in renewable energy projects. To achieve this, we utilize the variable weight matter-element extension model to establish the project’s fundamental reliability function. We then refine this model by incorporating evidence theory to assess the project’s risk level and derive precise risk index measurements. We utilize the GM model to forecast potential future risks associated with the project. In addition, a case study is presented on the risk assessment and prediction for the Maynak Hydropower Station. Our findings reveals that the project encountered significant investment risks in 2008, 2014, 2020, and 2022. Key risk indicators include political turmoil，policy change，imperfect legislation，cultural risk，exchange rate changes，technical risks and management risks. Furthermore, the investment risk level declined from 2023 to 2027, with our risk measurement outcomes closely aligning with actual conditions, thereby validating the effectiveness and applicability of our model.

Evaluation of Operational Safety Risk in Wastewater Treatment Plants Based on WSR and Matter–Element Extension Theory

Wastewater treatment plants are of significant importance in facilitating China’s urbanization process. The fundamental purpose of wastewater treatment plants is to control water pollution and protect the environment. It is therefore essential that they are operated in a safe manner in order to achieve this goal. In order to guarantee a systematic and objective assessment of the operational safety risks inherent to wastewater treatment plants, the Wuli–Shili–Renli (WSR) theory has been introduced. Accordingly, a three-dimensional evaluation index system was developed for the assessment of these risks. A combination of subjective and objective methods utilizing game theory was employed to determine comprehensive risk factor weights. Subsequently, the material–element extension theory model was implemented in a wastewater treatment plant situated in the northern region of the Changchun Development Zone. The assessment classified the plant as Level 1 (safe), although it was determined that improvements in accident prevention are necessary. This study presents a robust framework for operational safety assessment that contributes to enhanced risk management and the long-term reliability of wastewater treatment operations. The results of the sensitivity analyses provide substantial evidence of the reliability and validity of the model.

Comprehensive Evaluation and Decision-Making of Park Level Comprehensive Energy System Planning Scheme Based on Object Attributes and Matter Element Extension

Comprehensive Evaluation and Decision-Making of Park Level Comprehensive Energy System Planning Scheme Based on Object Attributes and Matter Element Extension

Integrated Evaluation Method of Bus Lane Traffic Benefit Based on Multi-Source Data

Bus lanes are an important measure for improving the quality of bus service and the efficiency of transportation systems. A scientific and reasonable evaluation of the overall traffic operation efficiency of the bus priority road section is helpful to fully understand the improvement effect of the introduction of bus lanes on traffic operation. To comprehensively and objectively evaluate the traffic benefits of bus lanes, the Delphi and grey correlation methods were used to construct a comprehensive weight calculation model of the indicators. The weights of eight traffic benefit evaluation indicators at the two levels of buses and general traffic were calculated, and the weights were then optimized using the target optimization model. Combined with different weight indexes, the evaluation of the traffic benefit level of the bus lane was realized using the matter-element extension model based on the improvement in the sticking progress. The bus lanes of the Daping-Yangjiaping, Huanghuayuan interchange-Luneng turntable, and Dashiba-Hongqihegou routes in the main urban area of Chongqing were used for verification. The results show that the traffic benefits of the three case areas have been improved to a certain extent after the construction of bus lanes, but the benefit level has not changed. Through the analysis of various operating indicators, the weaknesses that affect the traffic efficiency can be obtained, and then the decision-making basis for the implementation and improvement of the bus lane optimization scheme can be provided.

Research on Supplier Selection of Pharmaceutical Enterprises under the Dual Carbon Target

With the proposal of national carbon peak and carbon neutrality targets, green supply chain management has become one of the important means of reducing carbon emissions. Based on elaborating on the connotation of new quality productivity, this article analyzes the supplier selection problem of pharmaceutical enterprises under the dual carbon target. A pharmaceutical supplier evaluation index system has been established from five aspects related to low-carbon and environmental protection, including technological innovation, research and development capabilities, digitization, intelligent production, environmental protection technology, and so on, with five primary indicators and 18 secondary indicators. Secondly, a game theory combination weighting method combining the G1 method and entropy weight method is used to determine the weights of indicators. A pharmaceutical supplier evaluation model is established by combining the matter element extension model. A company is used as an example to evaluate its 8 candidate suppliers and select the best supplier. Finally, corresponding measures are proposed to promote the healthy and sustainable development of pharmaceutical enterprises.

Effect of expressway exit deceleration markings on distracted drivers in China

Expressway exit areas experience traffic diversion and complex road conditions, making them accident-prone areas. In this study, transverse and fishbone visual illusion deceleration markings were selected to optimize the induction facilities at expressway exits. The research aims to investigate the impact of these markings on the driving behavior, cognitive load, and physiological characteristics of drivers in various distracted scenarios at expressway exit areas. Furthermore, a comprehensive evaluation of each experimental scheme is conducted using the Matter-Element Extension Model. The study found that the implementation of deceleration markings can effectively enhance driver alertness and lane change awareness, enabling drivers to reduce their speed to near the speed limit in exit areas without compromising driving comfort. Compared to the situation without markings, drivers begin to decelerate approximately 600 m earlier and exit the ramp when markings are present. Fishbone deceleration markings, in contrast to transverse markings, result in lower vehicle speeds, smoother deceleration, and more effectively stimulate drivers' intention to change lanes, guiding them to make the final lane change earlier. Based on the comprehensive evaluation results, it is recommended that transverse or fishbone deceleration markings be considered in engineering practice. These markings have not produced significant effects on driver visual fatigue and driving load, with fishbone markings demonstrating superior comprehensive evaluation outcomes. These research findings can provide valuable insights for future expressway exit area marking design schemes, further enhancing driver safety.

Risk Assessment of TBM Construction Based on a Matter-Element Extension Model with Optimized Weight Distribution

In order to effectively address the potential hazards associated with the construction of Phase II of the YE Water Supply Project’s KS tunnel in Xinjiang, this study employs the WBS-RBS (Work Breakdown Structure and Risk Breakdown Structure) method for risk identification. This approach aims to identify various risks that may arise during TBM (Tunnel Boring Machine) construction. To prevent incomplete risk factor identification resulting from subjective judgment, a risk index system is established based on the identification results. Subsequently, a matter-element extension model is utilized to quantify the risk factors within this index system, and comprehensive weights are determined using variable weight theory to assess construction risk levels. Importance analysis of each index is then conducted to identify those with significant impact on risk evaluation outcomes. Finally, by comparing actual engineering cases with other risk evaluation models, this paper verifies the reliability of its constructed risk assessment model and proposes measures for controlling potential risks based on these evaluations. The paper provides a clear definition of safety risks encountered during TBM construction and conducts comprehensive risk assessments as a valuable reference for research related to the tunnel boring machine construction period in tunnel engineering.

Research on Safety Risk Assessment of Xi'an Metro Operation Based on Structural Equation Model (SEM)-Matter-Element Extension Model (MEA)

To ensure the safety of Xi'an Metro operation and improve the level of operational safety risk management, a comprehensive evaluation model of operational safety risk of Xi'an Metro based on structural equation model (SEM)-matter-element extension model (MEA) was established based on 4M theory. Firstly, by analyzing both domestic and international Metro accident cases and literature, four risk factor perspectives were identified as personnel, equipment, management, and environment. Secondly, to accurately assess the safety risk of Xi'an Metro operation, a risk evaluation index system consisting of four primary indicators, eleven secondary indicators and forty-four observation points was established. Finally, the index weights were determined using structural equation modeling, and a comprehensive evaluation utilizing the Matter-element extension model was conducted to obtain precise safety evaluation results. The model was applied to Xi'an Metro Line 2, and the results indicated that the operational safety level of Xi'an Metro Line 2 is relatively secure. According to the evaluation results above, the findings align with the current conditions. Xi'an Metro operating company can utilize these results as a point of reference to propose measures that correspond to varying risks. This will effectively reduce safety risks and ensure the safe operation of Xi'an Metro.

Research on investment selection of park-level integrated energy system considering electricity-heat-cooling-storage based on matter element extension

The park-level integrated energy system characterized by electricity heat cooling storage is regarded as a viable solution to energy and environmental crises due to its cleanliness and high efficiency. However, decision-makers encounter challenges in picking the optimum construction scheme. The paper introduces the matter element extension into the investment decision-making of the park-level integrated energy system. To begin, the paper analyzes the composition of the evaluation index system from the basic composition of the park-level integrated energy system, and establishes a standard system for comprehensive performance analysis, including economic, environmental, energy, security, and intelligence. Second, the subjective weight is calculated using the fuzzy analytic hierarchy process, the objective weight is calculated using the entropy weight. The matter element extension is used to evaluate the alternatives' performance. Finally, an industrial park in Jiangsu Province of China is selected as a case to verify. The results show that good comprehensive performance can be obtained by using photovoltaic, wind turbines, electric energy storage, ice storage, and heat pumps. The decision-making results will not be affected by the change in subjective and objective weight and the change in index weight within 20 %, but changes in matter-element classification would.

Integrated measurement of public safety risks in international construction projects in the belt and road initiative

PurposeThe purpose of this paper is to develop a comprehensive understanding of the public safety risks of international construction projects (ICPs) from the perspective of threat and vulnerability. A novel and comprehensive risk assessment approach is developed from a systemic perspective and applied to the Belt and Road Initiative (BRI) to improve the public safety risk management strategy for ICPs in BRI.Design/methodology/approachFirst, a public safety risk indicator system was constructed from the two dimensions, namely threat and vulnerability. Next, an integrated measurement model was constructed by combining the Genetic Algorithm-Backpropagation (GA-BP) neural network, fuzzy comprehensive evaluation method and matter-element extension (MME) method. Data from 49 countries involved in the BRI, as well as five typical projects, were used to validate the model. Finally, targeted risk prevention measures were identified for use at the national, enterprise and project levels.FindingsThe findings indicate that while the vulnerability risks of typical projects in each region of the BRI were generally low, threat risks were high in West Asia and North Africa, Commonwealth of Independent States (CIS) countries and South Asia.Originality/valueFirst, the structure of the public safety risk system of ICPs was analyzed using vulnerability and system theories. The connotation of public safety risk was defined based on two dimensions, namely threat and vulnerability. The idea of measuring threat risk with public data and measuring vulnerability risk with project data was clarified, and the risk measurement was integrated into the measurement results to help researchers and managers understand and systematically consider the public safety risks of ICPs. Second, a public safety risk indicator system was constructed, including 18 threat risk indicators and 14 vulnerability risk indicators to address the gaps in the existing research. The MEE model was employed to overcome the problem of incompatible indicator systems and provide stable and credible integrated measurement results. Finally, the whole-process public safety risk management scheme designed in this study can help to both provide a reference point for the Chinese enterprises and oversea contractors in market selection as well as improve ICP public safety risk management.

Electric Vehicle Supply Chain Risk Assessment Based on Combined Weights and an Improved Matter-Element Extension Model: The Chinese Case

In order to meet energy and environmental challenges, many countries will implement the replacement of fuel vehicles for the future clean energy transition; so, the number of electric vehicles (EVs) operating in cities will grow significantly. It is crucial to assess the risks of the electric vehicle supply chain (EVSC) and prevent them. Based on this, this paper proposes an EVSC risk research framework with combined weights and an improved matter-element extension model: (i) Firstly, the EVSC evaluation index system is constructed from the six stages of supply chain planning, sales, procurement, manufacturing, distribution, after-sales, and external risks. (ii) The subjective and objective weights are calculated by the decision laboratory method and entropy weight method, respectively, and then the minimum deviation method is used for a combined design to overcome the defects of a single method. (iii) An improved matter-element extension model (MEEM) is constructed by introducing asymmetric proximity degree and risk bias. (iv) The model is applied to a case study and its feasibility and superiority are verified through sensitivity analysis and comparative analysis. The final results show that the method and framework proposed in this paper are in line with EVSC risk assessment standards and superior to other models, which can help EVSC managers to identify potential risks, formulate appropriate risk prevention measures, promote the stable development of electric vehicles, and provide a reference for the development of energy and environment.

Comprehensive evaluation of digital village development in the context of rural revitalization: A case study from Jiangxi Province of China.

Digital rural construction is a key strategic direction to promote China's rural revitalization and alleviate global climate problems. In order to put forward feasible suggestions for the subsequent development and ensure the smooth development of digital village construction, how to reflect the development level of the digital village through scientific and reasonable comprehensive evaluation has become an urgent problem to be solved. This paper establishes a comprehensive evaluation index system through the Delphi method and principal component analysis method, then assigns weights to the evaluation indicators based on the improved CRITIC-G1 method, and then grades the development level of digital villages according to the extension matter element method. Finally, taking Jiangxi Province in China as an example, the overall development level of digital villages in Jiangxi Province is evaluated from the provincial level according to the proposed method. And put forward the corresponding countermeasures and suggestions. Results: Firstly, the development level of digital villages in Jiangxi Province is good, and there is a trend of excellent development level. Secondly, from different aspects of digital rural development, the digitalization of infrastructure, services, economy, and green production in Jiangxi Province is at a good level, and the digitalization of life has reached an excellent level. Thirdly, from the perspective of development trends, the digitization of infrastructure has a progressive trend towards an excellent level of development, while the digitization of services, economy and green production has signs of development regression. According to the analysis results, the relevant countermeasures and suggestions are put forward from four aspects: talent, capital, governance system and development planning. Other regions can evaluate the development level of the digital village according to the evaluation model proposed in this paper so as to analyze the existing problems and put forward targeted solutions to promote the construction of the digital village.

Application of Research on Risk Assessment of Roadway Roof Falls Based on Combined Weight Matter Element Extension Model

Roof falls in coal mine roadways are the main causes of many casualties, shutdowns and production plan delays. To understand the relationship between the influencing factors of roadway roof fall accidents and the importance ranking of the accidents, we will reduce safety accidents in coal mines. To enable the timely prediction and control of roadway roof fall risks, based on the investigation of many roadway roof fall risk factors, 12 evaluation indexes such as the roadway roof rock thickness, geological conditions and roadway section shape were selected. An evaluation index system of roadway roof fall risks is constructed. A risk degree standard of roadway roof falls is proposed. The risk evaluation model of roadway roof falls was established by using the combination weight of the analytic hierarchy process (AHP), entropy weight method (EW) and matter element extension theory. According to the principle of the maximum membership degree, the risk degree of roadway roof falls is determined. Based on Java Web, a risk assessment system for roadway roof falls was developed. We name the system Multiple Weight-Material Element Web (MW-MEW). The MW-MEW system was used to evaluate the risk degree of roof falls in the C9 return airway of the Xingu Coal Mine. Compared with the evaluation results of the AHP matter element extension model, it is found that the evaluation results of the MW-MEW system are more in line with the actual engineering conditions. The successful application of the MW-MEW system will provide new avenues for the quantitative evaluation of roof fall risks in coal mine roadways.

Air pollution concentration fuzzy evaluation based on evidence theory and the K-nearest neighbor algorithm

Background: Air pollution, characterized by complex spatiotemporal dynamics and inherent uncertainty, poses significant challenges in accurate air quality prediction, and current methodologies often fail to adequately address these complexities.Objective: This study presents a novel fuzzy modeling approach for estimating air pollution concentrations.Methods: This fuzzy evaluation method integrates an improved evidence theory with comprehensive weighting and the K-nearest neighbor (KNN) interval distance within the framework of the matter-element extension model. This involves generating the basic probability assignment (BPA) based on interval similarity, performing sequential fusion using the Dempster–Shafer evidence theory, enhancing the fusion results via comprehensive weighting, and conducting fuzzy evaluation of air pollution concentrations using the matter-element extension KNN interval distance.Results: Our method achieved significant improvements in monitoring air pollution concentrations, incorporating spatiotemporal factors and pollutant concentrations more effectively than existing methods. Implementing sequential fusion and subjective–objective weighting reduced the error rate by 38% relative to alternative methods.Discussion: Fusion of multi-source air pollution data via this method effectively mitigates inherent uncertainty and enhances the accuracy of the KNN method. It produces more comprehensive air pollution concentration fusion results, improving accuracy by considering spatiotemporal correlation, toxicity, and pollution levels. Compared to traditional air-quality indices, our approach achieves greater accuracy and better interpretability, making it possible to develop more effective air quality management strategies. Future research should focus on expanding the dataset to include more diverse geographical and meteorological conditions, further refining the model to integrate external factors like meteorological data and regional industrial activity, and improving computational efficiency for real-time applications.

Resilience evaluation of low-carbon supply chain based on improved matter-element extension model.

How to evaluate the resilience level and change trend of supply chain is an important research direction in current supply chain management practice. This paper proposes a new method of supply chain resilience assessment based on hesitant fuzzy linguistic term set (HFLTS) and matter element extension theory. Firstly, based on the research status quo at home and abroad, a low-carbon enterprise supply chain resilience assessment index system is established, which includes six first-level indicators and corresponding 21 second-level indicators of product supply resilience, resource resilience, partner resilience, information response resilience, financial resilience and knowledge resilience. Secondly, HFLTS was used to collect expert opinions and Ordered Weighted Arithmetic (OWA) to calculate the expert composite language, by which the fuzzy evaluation matrix of supply chain resilience assessment indicators was obtained. Once again, the resilience indicator weights are determined based on a game-theoretic portfolio assignment method combining the best-worst method (BWM) and the CRITIC method. Finally, the nearness degree function is combined with the extension comprehensive evaluation method to improve the matter element extension model, and the supply chain resilience assessment model of low-carbon enterprises based on the game theory combination assignment-improved matter element extension is established. Taking X low-carbon enterprise as an example, the evaluation results show that the supply chain resilience level of this enterprise is II, and the eigenvalue of the grade variable is 2.69, and the supply chain resilience is shifting to III, and the supply chain resilience is shifting to III, which indicates that the supply chain resilience of this enterprise is being enhanced. Therefore, the improved matter element extension not only ensures the accuracy of the evaluation results, but also has higher prediction accuracy.

Research on the evaluation of the operating effectiveness of the safety double prevention mechanism of coal mine enterprises based on matter-element extension

Safety production is a crucial guarantee for the country's economic development, and the safety double prevention mechanism is an effective way to realize safety production. In order to improve the operating effectiveness of coal mine enterprises' safety double prevention mechanism, this paper preliminarily constructs the evaluation indicator system for the operating effectiveness of the safety double prevention mechanism of coal mine enterprises based on the accident cases and literature analysis. The questionnaire was designed according to the index system, and the reliability and validity of the recovered data were analyzed. Based on the results of the analysis, the index system for evaluating the operating effectiveness of the safety double prevention mechanism of coal mine enterprises is established. This system comprises five first-level and 30 second‐level indicators for risk hierarchical control, hidden danger investigation and treatment, inspection review and update, employee safety management, and safety guarantee management. Subsequently, this paper utilized the AHP-EWM to empower the evaluation indicators and then constructed the matter-element extension model to evaluate the operating effectiveness of coal mine enterprises' safety double prevention mechanism. Finally, the Y coal mine enterprise is an example of empirical analysis. The results show that the operating effectiveness of the Y coal mine enterprise's safety double prevention mechanism has generally reached a good level. However, some evaluation indicators still have a low evaluation level, which is consistent with the actual situation of the Y coal mine enterprises. Evaluation results verify that this paper's evaluation indicators and model have strong applicability and scientificity.