Matter-element Extension Model Research Articles

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 meters 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.

Traffic safety comprehensive evaluation of urban tunnel visual guiding system based on extension matter-element model: a case study in tunnel curves

Objective The visual guiding system, as a tunnel traffic safety improvement method by using visual guiding facilities to actively guide driving safely, has been widely used in countries with many tunnels, in recent years. This paper aims to quantitatively study the comprehensive evaluation of traffic safety of the visual guiding system in tunnels, which has certain engineering application value and can provide support for the quantitative evaluation and optimal design of tunnel traffic safety. Methods Based on the analysis of the relevant factors of urban tunnel traffic safety, a multi-factor comprehensive evaluation system with 5 upper-level indicators and 12 basic-level indicators was proposed. Considering the independent and incompatible indicators, a comprehensive evaluation method of traffic safety of the visual guiding system in urban tunnels was constructed by using the extension matter-element model. Taking the scene of 4 types of tunnel curves, such as no facilities, horizontal stripe, chevron alignment sign, and LED arch, as examples, the comprehensive evaluation of various schemes were carried out by using simulation tests. Results The traffic safety comprehensive evaluation system of visual guiding system in urban tunnels can be analyzed from five aspects: perception reaction, guidance ability, driver factor, driving task, and facility appearance. The results demonstrated significant the comprehensive evaluation result of the target level of scene 1 was L4, scene 2 was L3, scene 3 was L2, and scene 4 was L1. That is, the final results of the comprehensive evaluation of the four scenes were poor, medium, good, and very good, respectively. Conclusions In the scheme of visual guiding system for urban tunnel curves, the effectiveness of the three types of designs, from high to low, was the LED arch, chevron alignment sign, and horizontal stripe, and the safety of the scene without facilities was the lowest. Hence, setting the LED arch in the urban tunnel curve has a good effect in the aspects of guidance ability, sight distance, and sight zone, and is conducive to the driver’s perception reaction and driving task.

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.

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.

Testability evaluation of radar equipment with improved matter-element extension method

In response to the problems of many influencing factors and different indexes, a radar equipment testability assessment index system is constructed based on the characteristics of equipment and testability connotation requirements. The Criteria Importance Though the Intercrieria Correlation (CRITIC) method is improved by using the variance coefficient to replace standard deviation and conflict coefficient to calculate the absolute value, and the objective weights of evaluation indexes are determined. An improved matter-element extension model is established, and the testability evaluation of different types of radar equipment is obtained by calculating the asymmetric close degree of the extension set. The effectiveness of the model is verified by an example analysis.

Multi-Level Prediction Framework of Driving Risk Based on the Matter-Element Extension Model

Surrogate safety measures (SSMs) can be used alone or in combination to assess vehicle conflicts. However, considering the complexity and uncertainty of the traffic environment, the road traffic factors that can be accounted for are still limited by combining two or more SSMs. This study proposes a driving risk prediction framework based on a modified matter-element extension model (MEEM), which integrates a set of carefully selected indicators at the macro-road-section level, the meso-vehicle-group level, and the micro-adjacent-vehicle level, to comprehensively reflect the factors affecting road traffic safety in temporal, spatial, and vehicular dimensions. To validate the proposed framework, lane-changing trajectories from the highD dataset are extracted to obtain the multi-level indicators and clustered risk levels. Different combinations of the multi-level indicators in different proportions are examined. The results show that the multi-level indicator combinations outperform those with micro-level indicators only, and optimal prediction performance is achieved when the ratio of meso- and micro-level indicators approaches 4:6. Furthermore, different time advances of the macro-level indicators are compared and analyzed considering flow propagation effect. It is found that an appropriate setting of the time advance in the calculation of macro-level indicators can help improve the accuracy of risk prediction. Finally, compared with the baseline algorithm random forest, MEEM generally shows better prediction performance at different prediction time, indicating that the multi-level indicators can be more effectively fused to assess risk using the proposed MEEM.

Dynamic Evaluation of Water Resources Management Performance in the Yangtze River Economic Belt

The evaluation of water resources management performance (WRMP) can provide guidance for water resources management. This paper constructs a scientific WRMP evaluation index system based on “water resources–water environment–water ecology”. Secondly, the game variable weight matter–element extension model is appropriately introduced to dynamically evaluate the WRMP level of the provinces (cities) in the YREB from 2012 to 2021, and Arcgis is used to analyze the spatial and temporal variations in the performance level of each sub-system. Lastly, a geographical detector model is used to explore the main factors influencing the WRMP in the Yangtze River Economic Balt (YREB). The main findings are as follows: (1) The overall provincial WRMP level in the YREB has been improving from 2012 to 2021, and the performance of water resource utilization (WRU) and water environment treatment (WET) are high in the east and low in the west, while the performance of water ecological protection (WEP) shows a trend of continuous improvement. (2) Compared with the model without variable weight modification, the game variable weight matter–element extension model can reflect the influence of the measured value of the index on the evaluation result as much as possible. (3) The top eight factors that have a greater impact on the WRMP level are the industrial water conservation rate, water resource development and utilization rate, water resource sustainability index, sewage diameter ratio, urban water penetration rate, industrial wastewater treatment completion rate, ecological construction and protection of the year to complete the investment in GDP, and the water ecological carrying capacity growth rate. The interaction types of each influence factor are nonlinear enhancement and two-factor enhancement.

Source Appointment and Assessment of Heavy Metal Pollution in Surface Dust in the Main District Bus Stops of Tianshui City

In this study, a PMF model was used to identify the sources and pollution level of heavy metals in the surface dust of a bus station. On the basis of the traditional heavy metal pollution evaluation methods, the Hakanson toxicity response coefficient was used to modify the traditional weight. The matter-element extension theory was introduced to reflect the toxicological properties and hazard degree of the heavy metals, and the matter-element extension model was established to evaluate the pollution level of heavy metals in the surface dust of the study area. The results were compared with Igeo, PN, and RI. ① Except for Co and V, the other heavy metals were higher than the Gansu soil background values by 1.29-9.30 times. The points of Cu and Pb exceeded the rate by 100%, and Cr, Ni, and As exceeded the rate by 96.15%, 94.23%, and 96.15%, respectively. ② PMF showed that source 1 was a natural source, and its contribution rate to V was 32.12%. Source 2 was natural-traffic pollution sources, contributing 51.50% and 33.37% to Cu and Co, respectively. Source 3 was a construction waste pollution source, with contribution rates of 45.06% and 44.70% for Cr and Ni, respectively, and source 4 was a coal-traffic mixed source, with contribution rates of 49.89% and 75.25% for As and Pb, respectively. ③ The matter-element evaluation results showed that the surface dust of the bus stops was mainly class IV (moderately polluted), and 13% of sample points were still clean, 37% were moderately polluted, and 25% were slightly and heavily polluted. The results of this method were quite different from the PN results and were more consistent with the RI results, indicating that its evaluation results were more sensitive and can be used for heavy metal pollution assessment.

A Predictive Method for Weak Signal Evolution During New Product Development Based on an Improved Matter-Element Extension Model

A Predictive Method for Weak Signal Evolution During New Product Development Based on an Improved Matter-Element Extension Model

Risk Assessment Method of Power Communication Network Based on Gray Cloud Theory and Matter-Element Extension Model Coupling

Risk Assessment Method of Power Communication Network Based on Gray Cloud Theory and Matter-Element Extension Model Coupling

RETRACTED: Luo et al. Evaluation of Soil Pollution by Potential Toxic Elements in Cultivated Land in the Poyang Lake Region Based on an Improved Matter–Element Extension Model. Forests 2022, 13, 1445

The journal retracts the article entitled ‘Evaluation of Soil Pollution by Potential Toxic Elements in Cultivated Land in the Poyang Lake Region Based on an Improved Matter–Element Extension Model’ [...]

Sustainability Assessment of Bus Low-Fare Policy Considering Three Stakeholders of the Public, Bus Enterprises and Government: A Case Study of Shenzhen, China

In order to quantitatively evaluate the sustainability of bus low-fare policy, this study establishes a sustainability evaluation index system for bus low-fare policy by using the PSR (Pressure–State–Response) model. Based on the matter–element extension model and entropy weight method, the sustainability evaluation model of bus low-fare policy is constructed. Finally, taking Shenzhen as an example, this study compares and analyzes the sustainability changes of bus fare policy in 2006, 2012 and 2016. The results show that the sustainability of the bus fare policy does not depend on the attribute of the fare (profit-making fares or public welfare fares): the sustainability of bus low-fare policy is closely related to the supporting fiscal subsidy system. Compared with the cost regulation subsidy system, the quota subsidy system is more conducive to the sustainability of bus low-fare policy. This study provides a decision-making reference for the sustainable development of urban bus low-fare policy.

A novel intelligent identification approach based on modified hierarchical diversity entropy and extension theory for diagnosis of rotating machinery faults

Aiming at the troubles of difficult extraction of fault features and low fault recognition rate in rotating equipment fault detection approach, a new technique for intelligent diagnosis based on modified hierarchical diversity entropy (MHDE) and extension theory (ET) is proposed in the thesis. Firstly, MHDE employs to comprehensively describe the fault information of the given signals. Secondly, the MHDE feature sets are regarded as the characteristic parameters of the extension matter element model, and the matter element model in various states is established. Finally, the testing datasets are fed into the matter element model for each operating conditions, and the correlation function is used to compute the comprehensive correlation between the testing datasets and the various conditions of the rotating machinery, so as to realize the qualitative and quantitative identification of the testing datasets. The reliability and superiority of the proposed new approach is validated by real experimental datasets on various rotating machinery types. The analysis results show that the proposed novel technology can effectively excavate the feature information and accurately identify various fault conditions of rotating machinery. In addition, compared with other combined model technology in the paper, the proposed intelligent fault diagnosis technology has better classification performance.

Risk Assessment of Mining Heritage Reuse in Public–Private-Partnership Mode Based on Improved Matter–Element Extension Model

With the development and utilization of resources, mineral-resource cities face the dilemma of resource depletion, the environmental restoration of mines, and industrial transformation. Reusing their mining heritage is a good way for these cities to change their mono-industrial structure and vigorously develop successor industries. Due to the complexity of reusing mining heritage, introducing the “Public–Private-Partnership” (PPP) mode can be a good solution to the problems of the government’s mining heritage reuse, such as large capital investment and a long construction-cycle time. To accurately classify the risk of reuse of mining heritage in the PPP mode, 26 indicators are selected to construct the evaluation index system of mining heritage reuse in the PPP mode based on five aspects: social capital-side, contractor-side, government-side, civilian-side, and the natural environment. The path coefficients of the structural equation model are used to calculate the weights of the indicators. The improved matter–element extension model is constructed to evaluate the reuse of mining heritage in the PPP mode. The Jiaozuo-Centennial Mining Heritage Park project is the object of research for applying the model. The results show that the risk evaluation index system combines the risk factors from the stakeholders’ perspective. The risk-evaluation model of the mining heritage reuse PPP project is constructed based on the combination of the improved matter–element extension model, the calculation of the asymmetric closeness, and the structural equation modeling method, which solves the drawbacks of the traditional model, such as the difficulty of determining the weights of the indicators, the incomplete scope of the material element domains, and the poor calculation of the comprehensive correlation degree. The case analysis shows that the risk level of the Jiaozuo-Centennial Mining Heritage Park project is Level II. This aligns with the actual situation and verifies the feasibility of the risk-evaluation model applied to the actual project. The research in this paper fills the gap in the risk model of mining heritage reuse in the PPP mode, enriches the theoretical system of risk evaluation of mining heritage reuse projects, and provides reference significance for similar mining heritage development projects in the future.

Research on the Evaluation of Emergency Management Synergy Capability of Coal Mines Based on the Entropy Weight Matter-Element Extension Model

Emergency management synergy capability is not only a “touchstone” to measure the operation effect of the emergency system of coal mine enterprises, it is an important symbol to reflect its level. In order to improve the level of emergency management in coal mines based on the PPRR theory of crisis management cycle, in this paper a hierarchical evaluation index system is constructed based on the emergency management process. A quantitative evaluation model of emergency synergy capacity is proposes based on the entropy–weighted elemental topology method to conduct evaluation and model validation for the case of J coal mine in Henan Province. The results show that the overall evaluation of the emergency management synergy capability of J Coal Mine is at a “good” level, with the emergency prevention synergy capability, emergency preparedness synergy capability, and recovery and reconstruction synergy capability at a “good” level and the emergency response synergy capability is at a “average” level. This indicates that the evaluation model is consistent with the current development of coal mining enterprises and has universal applicability. Therefore, this research can provide decision-making support for emergency management synergistic capacity building of coal mining enterprises to enhance the inherent driving force behind the early completion of the dual carbon task in the coal mining industry.