Evaluation Index System Research Articles

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.

Navigating the complexity of tram ride comfort assessment in growing urban environments: A cloud theory perspective

AbstractThis study addresses the challenge of quantitatively assessing ride comfort in tram travel in Growing Urban Environments, where multiple influencing factors complicate developing a unified evaluation index system. A comprehensive evaluation framework based on cloud theory is proposed to overcome this challenge. The approach involves defining five‐level comfort evaluation grades to capture passengers' experiences and perceptions accurately. The Criteria Importance through Inter‐Criteria Correlation (CRITIC) method is employed to ensure objectivity to establish objective weights for evaluation indices. Subsequently, a cloud model algorithm is utilized to generate evaluation benchmark and actual result clouds, providing intuitive representations of the evaluation outcomes. The efficacy and rationality of the methodology is illustrated through a case study focusing on Suzhou Tram Line 2. This research contributes valuable insights for enhancing public transportation experiences in new urban settings by offering a systematic and objective approach to assessing tram ride comfort.

Evaluation of Thermal and Mechanical Properties of Foamed Phosphogypsum-Based Cementitious Materials for Well Cementing in Hydrate Reservoirs

As detrimental byproduct waste generated during the production of fertilizers, phosphogypsum can be harmlessly treated by producing phosphogypsum-based cementitious materials (PGCs) for offshore well cementing in hydrate reservoirs. To be specific, the excellent mechanical properties of PGCs significantly promote wellbore stability. And the preeminent temperature control performance of PGCs helps to control undesirable gas channeling, increasing the formation stability of natural gas hydrate (NGH) reservoirs. Notably, to further enhance temperature control performance, foaming agents are added to PGCs to increase porosity, which however reduces the compressive strength and increases the risk of wellbore instability. Therefore, the synergetic effect between temperature control performance and mechanical properties should be quantitatively evaluated to enhance the overall performance of foamed PGCs for well cementing in NGH reservoirs. But so far, most existing studies of foamed PGCs are limited to experimental work and ignore the synergetic effect. Motivated by this, we combine experimental work with theoretical work to investigate the correlations between the porosity, temperature control performance, and mechanical properties of foamed PGCs. Specifically, the thermal conductivity and compressive strength of foamed PGCs are accurately determined through experimental measurements, then theoretical models are proposed to make up for the non-repeatability of experiments. The results show that, when the porosity increases from 6% to 70%, the 7 d and 28 d compressive strengths of foamed PGCs respectively decrease from 21.3 MPa to 0.9 MPa and from 23.5 MPa to 1.0 MPa, and the thermal conductivity decreases from 0.33 W·m−1·K−1 to 0.12 W·m−1·K−1. Additionally, an overall performance index evaluation system is established, advancing the application of foamed PGCs for well cementing in NGH reservoirs and promoting the recycling of phosphogypsum.

Intuitionistic Connection Cloud Model Based on Rough Set for Evaluation of the Shrinkage–Swelling of Untreated and Lime-Treated Expansive Clays

The evaluation of the shrinkage–swelling characteristic of expansive clay is of great significance, but it is a complex problem since the evaluation process involves numerous uncertain factors, such as randomness, non-subordination, and hesitation uncertainties. Here, an intuitionistic connection cloud model has been proposed to address this issue. First, an evaluation index system is established. According to the reliability of interval-valued evaluation indexes, the corresponding cloud numerical characteristic parameters are specified based on the membership interval generated by the intuitionistic fuzzy principle. Moreover, the improved conditional information entropy based on rough set theory is utilized to assign the index weight. Subsequently, combined with the weight, the intuitionistic connection degree of the sample to the classification standard is determined to identify the shrinkage–swelling grade. Finally, a case study on the shrinkage–swelling grade of untreated and lime-treated expansive clays in Hefei Xinqiao International Airport was performed to illustrate the validity and reliability of the model. The results show that the proposed model is reasonable and feasible for the evaluation of the shrinkage–swelling grade of untreated and lime-treated expansive clays.

Emergy-Theory-Based Evaluation of Typhoon Disaster Risk in China’s Coastal Zone

The evaluation of typhoon disaster risk is a widely discussed global topic. Currently, the index system method has become a common approach for the evaluation of typhoon disaster risk. However, the indices within the system are calculated independently, and subjective human factors significantly influence the assignment of index weights. The existing studies lack purely quantitative assessment methods, which makes the studies less precise and more difficult for other researchers to replicate. To bridge this gap, this study employs emergy analysis methods based on thermodynamics to develop a typhoon disaster risk evaluation index system for China’s coastal zone. Without the interference of weights and other human factors, the system contains various quantitative indices, including aggregate impelling energy, typhoon intensity emergy, adaptability emergy, the vulnerability index, and the integrated typhoon hazard index. Subsequently, these indices and socio-economic data were spatialized, and the evaluation of typhoon disaster risk was conducted at the city grid level in the coastal zone of China. The findings reveal that the high-risk areas for typhoon disasters in China are concentrated in prefecture-level cities along the southeast coast. The typhoon disaster risk index is higher in the southern region compared to the northern region, with a decreasing trend in the distribution of the integrated typhoon hazard index from coastal to inland areas. The aim of this study is to use a new quantitative evaluation method (emergy) to evaluate typhoon disasters. It also serves as a theoretical foundation and technical support for national and local governments in the formulation of policies for disaster prevention and reduction.

Research on the Coupling Coordination and Driving Mechanisms of New-Type Urbanization and the Ecological Environment in China’s Yangtze River Delta

For high-quality growth to occur, new-type urbanization and environmental preservation must coexist and advance at the same time. The focus has shifted to maintain a balance between ecological quality and urbanization growth. This study focuses on the Yangtze River Delta (YRD) in China, utilizing panel data from 41 cities in the YRD spanning from 2009 to 2021 to construct evaluation index systems for new (type of) urbanization and ecological environment. To analyze spatial-temporal evolutionary aspects and determine the causes of the degree of coupling coordination between new-type urbanization and the ecological environment, methodologies such as the entropy weight method, coupled coordination degree model, and Tobit regression approach were used. The results show that (1) economic urbanization has experienced the most growth in the level of new-type urbanization in the YRD, which has been steadily increasing. Moreover, the ecological environment evaluation score increased from 0.581 in 2009 to 0.701 in 2021, revealing a cyclical pattern of increase and decrease in its evolutionary trajectory. (2) Within the scope of the study, the overall coupling coordination degree between new-type urbanization and ecological environment has increased, with the average value rising from 0.512 in 2009 to 0.540 in 2021. In comparison to Lishui, Huaibei, Huainan, Ningbo, Chuzhou, and Bozhou saw a greater increase in coupling and coordination degree, with pronounced variations and clustering patterns visible in their spatial distribution. (3) According to the Tobit regression analysis, the level of economic development, technological progress, industrial concentration, global openness, and educational investment had significant positive effects on the degree of coupled coordination between new-type urbanization and the ecological environment in the YRD, whereas the level of information technology did not reach the significance threshold. The findings of the study are crucial for establishing a regional framework for green and sustainable development, as well as for facilitating the coordinated growth of new-type urbanization and ecological environment. These findings hold great potential for driving positive change in both urban development and environmental conservation efforts.

Spatial quality measurement of commercial streets in old cities of medium-sized cities in China

ABSTRACT Chinese urban development has entered the stage of stock planning, and as an important part of urban public space, the construction of street space has a direct impact on urban development. High-quality street space contributes to sustainable urban development.High-quality street spaces are highly important for constructing vibrant and sustainable cities. Taking Jiaozuo city, a medium-sized city, as an example, this article establishes an evaluation index system for commercial street space quality from the aspects of external characterization and objective material space and uses the Pearson correlation coefficient to explore the influencing factors of urban commercial street space quality. This study finds that (1) crowd activities on commercial streets have different temporal and spatial patterns on weekdays and days off; (2) the external characterization of urban street space quality has a significant positive correlation with objective material spatial elements such as the density of public transportation stops, functional density, functional mixing, interface continuity, and spatial green visibility rate; (3) the enhancement of street accessibility and fine-tuning of functions are key to improving the spatial quality of commercial streets.This study provides theoretical basis and ideas for improving the spatial quality of commercial streets in medium-sized cities in China and promoting sustainable urban development.

Investigation of the Coupling and Coordination Relationship of Water–Energy–Food–Ecology and the Driving Mechanism in Dalad Banner

Aiming at the complex problems of water resources, energy, food, and ecology in ten parallel tributaries directly joining the Yellow River in Ordos City, Inner Mongolia Autonomous Region (the Ten Kongduis), the coordination of the water–energy–food–ecology (WEFE) system in Dalad Banner and its townships was studied from the perspective of system coupling in time and space. First, the evaluation index system of WEFE coupling coordination is constructed, and then the coupling coordination degree model, grey relationship degree model, and geographical detector are used to quantitatively evaluate the development level and spatio-temporal evolution characteristics of WEFE coordination in Dalad Banner and its townships and explore its driving mechanism. The results suggest that (1) the WEFE comprehensive evaluation index of Dalad Banner and its townships showed a slowly rising trend on the whole. The growth trends for the WEFE subsystems and integrated assessment are 0.65%, 21.02%, 17.01%, 1.17%, and 9.96%, respectively. This shows that the energy subsystem occupies the main position. (2) The coupling degree of WEFE in Dalad Banner and its townships is high; the mean value is 0.967, which is in the high-level coupling stage. But the coordination degree is low; the mean value is 0.668, which is in the elementary coordination stage. The spatial development is unbalanced and uncoordinated in Dalad Banner; this phenomenon mainly exists in the eastern part of Dalad Banner, with a gradual change from the west to the center of the area with higher harmonization. (3) The coordination of the WEFE system of Dalad Banner and its townships shows a good trend. The average coupling coordination degree in Wangaizhao town has the largest increasing trend, which is 12.69%. Fengshuiliang Town has the smallest growth trend, which is −10.37%. The region is gradually developing to the stage of well coordination, and each township has basically entered the middle-rank coordination stage. (4) In general, in the degree of system impact, the ecological impact is the largest and the grain is the weakest. In terms of spatial differences, energy has the greatest impact, while water has the least explanatory power. In terms of interaction, the interaction among water resources, grain, and ecology has the greatest explanatory power. The influence of WEFE in Dalad Banner coupling coordination changes obviously with time, and the driving mechanism and stability are relatively weak. The results of this study can provide a decision basis for the coordinated development of WEFE and the high-quality and sustainable development of Dalad Banner and its townships.

Higher education quality evaluation based on neural network model

With the constant goal of improving the quality of higher education, quality evaluation is a widely concerned problem, prompting this study to construct a higher education quality evaluation method based on a neural network model. First, an Attention Relevance Confidence Satisfaction (ARCS) model was constructed herein. This was done through two rounds of screening; the evaluation indexes of higher education quality were selected, and an evaluation index system was finally constructed. Then, the weight of each evaluation index was calculated using the constructed ARCS model. According to the 1–9 grading scale, an index scoring matrix of industry-education integration was established. Afterwards, the higher education quality evaluation score was obtained based on the neural network model, and the evaluation effect level was determined. The experimental results showed that the quality evaluation effect of the proposed method in the past five years showed an overall rising trend, even already reaching the top level. Moreover, the denoised experimental dataset was finally divided into a test dataset (28%) and an experimental dataset (72%), with the proposed method exhibiting a favorable effect.

Measurement and characteristics of high-quality development level of innovation and entrepreneurship based on EM-AHP-TOPSIS

By constructing an evaluation system for the high-quality development of innovation and entrepreneurship, an evaluation index system was established in this study from five aspects: the background, process, input, output, and transformation of innovation and entrepreneurship, and analytic hierarchy process (AHP) and entropy method (EM) were adopted to perform combination weighting. Then, the core of each subsystem and the comprehensive score were calculated based on the TOPSIS method, the high-quality development level of urban innovation and entrepreneurship in 19 vice-ministerial cities like Beijing, Shanghai, Tianjin, Chongqing, Guangzhou, Shenzhen, and Chengdu in China was measured, and the innovation and entrepreneurship development level and structural characteristics were analyzed from five aspects. The results show that Shenzhen, Shanghai, Beijing, Nanjing, and Guangzhou take the lead in the high-quality development of innovation and entrepreneurship, while Xi’an, Chengdu, Hangzhou, Wuhan, Qingdao, Jinan, and Ningbo are in the medium level. Chongqing, Shenyang, Dalian, Harbin, Xiamen, and Changchun perform poorly in the development of innovation and entrepreneurship with problems of interregional large gradient difference in capacity and unbalanced development, which provides an important reference for understanding the current situation, advantages, and disadvantages of innovation and entrepreneurship education development in various economic zones.

Difference in regional logistics development level in China based on entropy weight TOPSIS and Dagum models

The high-quality development of the logistics industry, which is an essential and strategic industry supporting the national economic operation and a fundamental component of modern industrial system construction, is not only a key component of the high-quality development of the national economy but also the main driving force for the high-quality growth of the national economy. As the supporting industry of the national economy, the logistics industry will also face spatial disequilibrium during development. Therefore, to achieve the coordinated development of the logistics industry, the high-quality development and the spatial-temporal unbalanced development status of the logistics industry in each province must be figured out first. This research established a comprehensive evaluation system for the logistics industry development, which included 14 basic indexes based on the provincial-level panel data of 30 provinces in China during 2009–2020. Then, the regional logistics development level score in China was measured using the entropy weight TOPSIS method, and the differences in the regional logistics development level in China and the dynamic evolution law of their distribution were deeply explored through the Dagum Gini coefficient model. The research results revealed that the evaluation index system (14 basic indexes) for the regional logistics industry development level in China was relatively scientific and reasonable; the regional logistics industry development level in China was increasing year by year, showing a steady upward trend, and the imbalance in the eastern, central, and western regions regarding the regional logistics development was shrinking year by year; the average intergroup contribution rate was 36.33%, the intragroup contribution rate was 31.49%, and the contribution rate of intensity of trans variation was 32.19%, proving that the regional differences exerted a most extraordinary influence on the spatial differences in the regional logistics industry development level in China. The research results have important reference value for summarizing the meaning of high-quality logistics industry development, constructing the evaluation index system for logistics industry development, and exploring the reasons for the temporal and spatial differences in logistics industry development in China.

Spatio-Temporal Evolution and Driving Factors of Tourism Economic Resilience in the Yili River Valley

The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. The purpose of this study is to construct a tourism economic resilience evaluation index system and assess the tourism economic resilience of 10 counties and cities in the Ili River Valley from 2010 to 2019 using the entropy weight TOPSIS method. The results show that (1) the tourism economic resilience shows a “W”-shaped time-series dynamic development trend, especially a decline in 2012–2013 and 2015–2016; (2) the spatial pattern shows a non-equilibrium characteristic, with the northwestern part of the valley represented by Yining City showing a high level of resilience, and the central to southeastern counties and cities showing a lower level of resilience; (3) the spatio-temporal evolution steadily points to “northwest–southeast”, and there are five toughness convergence clubs, with obvious stability and neighborhood effects; (4) and the analysis of the driving factors shows that the number of employees in the tertiary industry, especially the input of high-quality talents, is crucial to improving the quality of services, strengthening the ability to withstand risks and the potential for development, and its impact is significant. These results provide an important reference for the formulation of tourism development strategies and promote the sustainable development of tourism.

Partially ordered set evaluation of logistics competitiveness of coastal port cites considering carbon emissions

Aiming at the problem of logistics competitiveness of coastal cities, a logistics competitiveness evaluation method based on weighted and partially ordered set combinations is proposed. Carbon emissions and inhalable pollutant concentrations are included in the evaluation scope, and an evaluation index system for the logistics competitiveness of 17 coastal port cities is constructed. The results show that: (1) the competitiveness of the logistics industry in 17 coastal port cities in China has been continuously improved, and the catch-up effect of logistics industry development in coastal port cities such as Shenzhen, Ningbo and Qingdao is obvious. The competitiveness level of the logistics industry shows an obvious spatial imbalance. (2) The competitiveness of the logistics industry in Yingkou, Beibu Gulf and other coastal port cities is low, and the difference in competitiveness of the logistics industry in coastal port cities is the main reason for the overall imbalance. (3) The technological innovation, openness and economic development level of the city and the hinterland have a positive impact on the competitiveness of the logistics industry, and the level of economic development has the greatest contribution to the variance of the competitiveness of the logistics industry. The logistics competitiveness of 17 cities is ranked and classified. The leading cities have core diffusion effects and promote the development of the competitiveness of each city. Suggestions on improving the competitiveness of cities are conducive to the high-quality development of China’s logistics industry.

Evaluation of Green Suppliers Based on a Hybrid Weighting Approach and GRA Method

To align with the national dual carbon strategy and facilitate low-carbon production for enterprises, this paper incorporates the concept of green supply chain management and develops a scientifically sound evaluation index system for green suppliers by comprehensively considering five factors: quality, availability, cost, environmental management performance, and technology. The analytic hierarchy process and entropy weight method are employed to assign subjective and objective weights to each evaluation index while the grey correlation degree analysis method is utilized to rank and sort suppliers in order to select the optimal green supplier. Finally, an empirical example is presented to verify the reliability of our model.

Not Just Survive, But Thrive: Examining Livelihood Capital, Poverty Reduction, and Sustainable Development in Ethnic Tourism Destinations

Understanding the roles of tourism development in poverty reduction and livelihood capital through a microlens is essential to rural ethnic areas’ sustainable development. However, few assessment methods are available to unravel the complex relationships between these three facets, and gaps remain in measuring residents’ livelihood. Based on the sustainable livelihood approach, this paper first selected core components of the sustainable livelihood framework to construct an evaluation index system and then provided specific indicators and evaluative criteria. Taking villages in China’s Longji Rice Terraces as a sample case, this study employed objective approaches (e.g., the entropy weight method and gray relational analysis) to assess residents’ livelihood capital. The aim was to showcase the sustainability of this area’s livelihood through a microlens. Findings offer several important contributions. First, this study presents a reliable measurement development method and a set of evaluation criteria for sustainable livelihood in tourism contexts, including five forms of capital and 21 indicators. Second, local inhabitants were found to benefit from tourism development; their livelihood options were diversified, especially in terms of growing financial capital. Yet these benefits were not evenly distributed, with notable differences observed across communities. Third, farmers’ livelihood capability did not improve uniformly over time. These findings offer valuable insights for tourism and hospitality stakeholders and can help steer rural regions toward a path of prosperity and growth. Strategies for inspiring entrepreneurship should especially be considered. In closing, theoretical implications are discussed, and suggestions for future work are provided.

Evaluation and Selection of Manufacturing Suppliers under the Perspective of Smart Manufacturing Combined with Bilevel Programming

To address the issue of supplier evaluation and selection in the current intelligent manufacturing industry, a supplier intelligent evaluation and selection model combining bilevel programming is proposed. Firstly, based on existing research results and the current situation of the manufacturing market, a manufacturing supplier evaluation index system is constructed, and the principal component analysis method is used to simplify it; Then, the simplified indicator system is input into the back propagation neural network to build a supplier intelligent evaluation model and achieve supplier intelligent evaluation; A mathematical model for supplier selection problem is constructed based on bilevel programming, and an optimized sparrow search algorithm is put forward to solve it. A supplier intelligent selection model is constructed to achieve intelligent supplier selection. The lab findings denote that the F1 value of the supplier intelligent evaluation model is 0.953, the accuracy is 0.985, the area under the curve is 0.962, and the error of the output comprehensive evaluation value is 0.003; The output accuracy of the supplier intelligent selection model is 0.8. The above results indicate that the model raised in the article has good application effects in supplier evaluation and selection, and has a certain promoting effect on the development of the intelligent manufacturing industry.

Development and Mode Innovation of Cultural Tourism Resource based on Industrial Integration

The cultural tourism industry contributes to the growth of both cultural and tourism industries. Cultural Tourism Resource (CTR) is the prerequisite for the integrated development of the cultural tourism industry. Developing potential CTR can promote the new transformation and upgrading of the urban cultural tourism industry. Luoyang has the advantages of location and resources in the development of CTR, but its tourism industry develops slowly. Therefore, Luoyang City was taken as the research object and the relevant evaluation index system was established. The entropy method and grey correlation model were used to analyze the development trend and influencing factors of the city’s CTR. The entropy values of the eight indicators of the evaluation system of CTR established in the study were all above 0.96, indicating that the evaluation system was relatively stable. The grey correlation degree of CTR of historical culture and folk customs was high, which was 0.668 and 0.642, respectively. The grey correlation degree of religious culture and calligraphy and painting CTR was low, which was 0.625 and 0.617, respectively. The CTR of historical culture and folk customs have developed well, but the resources of religious culture, calligraphy, and painting need to be improved. The knowledge of cultural tourism location theory and regional economic growth theory are applied. According to the evaluation results and problems of the development of CTR in Luoyang, this paper puts forward targeted strategies for CTR.

Research on a Multi-Dimensional Indicator Assessment Model for Evaluating Landslide Risk near Large Alpine Reservoirs

Geological disasters in large alpine reservoirs primarily take the form of landslide occurrences and are predominantly induced by slope instability. Presently, risk monitoring and assessment strategies tend to prioritize sudden alerts overlooking progressive trajectories from the onset of creeping deformations within the slope to its critical state preceding landslides. Hence, analyzing landslide safety risks over time demonstrates a significant degree of hysteresis, highlighting the necessity for a comprehensive approach to risk assessment that encompasses both gradual and sudden precursors to landslide events. This study analyzes the factors affecting slope stability and establishes a slope evaluation indicator system that includes terrain morphology, meteorological conditions, the ecological environment, soil conditions, human activity, and external manifestation. It proposes a quantitative model for slope landslide risk assessment based on a fuzzy broad learning system, aiming to accurately assess slopes with different risk levels. The overall assessment accuracy rate reaches 92.08%. This multi-dimensional risk assessment model provides long-term monitoring of slope conditions and scientific guidance on landslide risk management and disaster prevention and mitigation on a long time scale for risky slopes in reservoir areas.

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.

Operational Risk Assessment of Engineering Vehicles Considering Driver Characteristics

As vehicles with high accident and casualty rates within the road transportation system, engineering vehicles have been receiving much attention and emphasis in terms of safety. Accurate analyses and evaluations of risk factors in vehicle operation are imperative for enhancing the management level of engineering vehicles. This study explores the differences between various types of drivers by analyzing the driving characteristics of professional drivers. The evaluation index system is developed and quantified by integrating factors related to engineering vehicle drivers, road environment, and industry management. Additionally, the risk assessment model is developed using the error backpropagation algorithm. The optimal model is determined by comparing the number of nodes in different hidden layers, the activation function, and regularization optimization. The prediction accuracy of this model’s coefficient of determination is 0.912, indicating that the model has validity. This study is conducive to improving the safety level of engineering vehicle operation in order to reduce the rate of vehicle traffic accidents, the severity of accidents, and the consequences of losses. It also has practical application value in safeguarding social security.