Risk Assessment Index System Research Articles

Research on quantitative risk assessment method of dust explosion based on Bayesian network

In order to effectively prevent the occurrence of dust explosion accidents in industrial enterprises and reducing the risk of dust explosion accidents, the article builds dust explosion risk assessment index system for industrial enterprises, taking Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) as theoretical basis and establishes dust explosion risk Bow-Tie Analysis (BT) diagram model. Mapping BT model into Bayesian Networks (BN) reveals the coupling mechanism of dust explosion risk nodes and constructs a generic dust explosion risk assessment BN model, which provides a quantitative assessment of the probability of occurrence of dust explosion accidents. The causative mechanism of dust explosion accidents is investigated by learning risk inference from this model. It is also demonstrated that appropriate safety barrier measures can effectively reduce the probability of accidents, thereby changing the accident level and improving the safety and reliability of the system. Finally, the validity and applicability of the model is verified through empirical analyses. The research results contribute to the scientific prediction of the probability of dust explosion risk and reasoning learning, which provides a scientific basis for enterprises to formulate effective dust explosion safety measures as well as to realize the hierarchical control of dust explosion risk.

Laboratory Risk Assessment Based on SHELL-HACCP-Cloud Model

With the increasing demand and expanding scale of laboratories in colleges and universities, laboratory accidents frequently occur, seriously impacting personal health, schools, society, and the environment. Scientific and effective risk assessment is crucial to prevent accidents. Therefore, in order to effectively reduce the risk of chemical laboratories and minimize the frequency of accidents. This study employs the combination of the SHELL model and HACCP system to analyze the potential sources of hazards in hazardous chemical laboratories and establish a risk assessment index system. Based on the Cloud model, a dynamic risk assessment model for the laboratory is established to quantitatively evaluate the risk level of the evaluation results. In order to ensure the rationality of the assessment results, the subjective and objective weights are combined by the principle of minimizing information entropy. Case analysis proves the scientific validity of the evaluation results of the model, which can assist laboratory managers in formulating emergency plans and risk management mechanisms to reduce or eliminate the occurrence of experimental accidents. This approach ensures the safe and sustainable development of schools and laboratories, which is conducive to the progress of researchers’ scientific research results.

Comprehensive risk management of health, safety and environment for social emergency rescue organization

During the rescue and relief work of social emergency rescue organizations, the rescue team members face significant responsibilities and risks. Social rescue organizations need to improve funding, available equipment and other aspects compared with professional emergency rescue organizations. Moreover, the development of rescue levels among emergency rescue organizations is unbalanced, and rescue teams’' comprehensive quality and skills are uneven. To understand the safety risks of these organizations before the implementation of rescue and relief tasks, the task situation and its characteristics must be assessed timely, and safety must be ensured under the premise of efficient completion of the rescue missions. Based on the theory of safety system engineering and health, safety, and environment risk management, a risk management model is established to achieve a closed-loop risk management. The risk factors in rescue and relief tasks of social rescue organizations were identified, and a health, safety and environment risk assessment index system and grading standard were established. A gray cloud model was applied for the evaluation method, the problems of information randomness, risk-level boundary fuzziness and randomness of the evaluation index data were effectively solved. Subsequently, a risk hierarchical early warning and control strategies were proposed to allocate emergency resources rationally. The proposed method was verified and found to have universal applicability and strong practicability.

Potential Risk Identification of Agricultural Nonpoint Source Pollution: A Case Study of Yichang City, Hubei Province

Potential risk identification of agricultural nonpoint source pollution (ANPSP) is essential for pollution control and sustainable agriculture. Herein, we propose a novel method for potential risk identification of ANPSP via a comprehensive analysis of risk sources and sink factors. A potential risk assessment index system (PRAIS) was established. The proposed method was used to systematically evaluate the potential risk level of ANPSP of Yichang City, Hubei Province. The potential risk of ANPSP in Yichang City was 18.86%. High-risk areas account for 4.95% and have characteristics such as high nitrogen and phosphorus application rates, large soil erosion factors, and low vegetation coverage. Compared with the identification results of the Diffuse Pollution estimation with the Remote Sensing (DPeRS) model, the area difference of the same risk level calculated by the PRAIS was reduced by 33.9% on average. This indicates that PRAIS has the same level of accuracy as the DPeRS model in identifying potential risks of ANPSP. Thus, a rapid and efficient identification system of potential risks of regional ANPSP was achieved.

Static and dynamic fuzzy assessment methods for the collapse risk of mountain tunnel construction

The static risk assessment method has difficulty tracking variations of the risk level, which is not conducive to the dynamic control of construction. Tunnel collapse during the construction of mountain tunnels has a dynamic evolution law and contains great risk of harm, and the corresponding dynamic risk assessment is extremely important. This study proposes a static and dynamic fuzzy uncertainty assessment method for the collapse risk of mountain tunnels. First, 150 tunnel collapse accidents were investigated and analysed, and the static and dynamic risk assessment index system of mountain tunnel construction collapse was established. Second, the DEMATEL method is processed by applying fuzzy logic, the subjective weight of each index is calculated, and the interaction between the indexes is analysed. Finally, the traditional VIKOR method is improved upon, and the weight of each assessment index is coupled and analysed. A static and dynamic uncertainty assessment model of the construction collapse risk of multiple construction sections is constructed. This method has been successfully applied to the risk assessment of tunnel collapse, and the assessment results are consistent with the actual construction situation. This study provides a new method for the static and dynamic assessment of mountain tunnel collapse risk.

Evaluation of Flooding Disaster Risks for Subway Stations Based on the PSR Cloud Model

This study aims to scientifically evaluate the risk of rainstorm waterlogging disasters in urban subway stations, improve the management of disaster prevention and control, and mitigate the impact of such disasters. To achieve this, a risk assessment analysis was conducted using the Pressure-State-Response (PSR) cloud model. The analysis involved examining the components of the subway station rainstorm waterlogging disaster system, including the disaster-prone environment, disaster-affected body, and disaster-causing factors. Based on the PSR framework, a risk assessment index system for rainstorm waterlogging disasters in subway stations was developed. The entropy weight method and cloud model algorithm were then combined to establish a risk assessment method. By utilizing a cloud generator, the digital characteristics of the risk cloud were calculated, and a risk cloud map was generated to determine the level of risk. Finally, an empirical analysis was carried out at Jin’anqiao Station of the Beijing Subway, providing valuable insights for the evaluation of rainstorm waterlogging disasters in subway stations.

Ecological risk assessment and management for riverfront development along the Yangtze River in Jiangsu Province, China

The riverfront along large rivers, representing the water–land and human–nature interaction zone, is of great importance for economic and social development and eco-environmental protection. Human activities, such as urbanization and industrialization, together with inadequate urban planning and disorderly development, can result in serious ecological risks to riverfront ecosystems. The focus of this study was the riverfront along the Yangtze River in Jiangsu province, an area experiencing conflicting demands in terms of ecological protection and economic development. We identified the ecological problems and risks at different spatial scales (micro, meso, and macro) and, based on PSR model, construct an ecological risk assessment index system for any further development along the Yangtze River. Ecological hot spots and cluster zones were identified based on Getis-Ord Gi* hot spot analysis and Ward’s hierarchical clustering. The results showed that the ecological risk index at micro scale of the study area presented spatially positive correlation, with hot spots mainly concentrated in municipal districts. The hot spots of ecological risk assessment at the meso-scale are distributed in the estuary around the Yangtze River, and the cold spots are distributed on the Yang-Tai plain. According to the assessment indices of social economy, ecological function, and planning response at the macro scale, the study area could be divided into four clusters. Lastly, a spatial division of ecological risk posed by riverfront development along the Yangtze River in Jiangsu Province was constructed. On the basis of this analysis, we propose suitable risk management and resource protection measures.

Flood Risk Assessment Based on a Cloud Model in Sichuan Province, China

Floods are serious threats to the safety of people’s lives and property. This paper systematically introduces the basic theories and methods of flood risk assessment, takes Sichuan Province as the study area, and establishes a flood risk assessment index system with 14 indicators in four aspects—disaster-causing factors, disaster-forming environment, disaster-bearing body, and regional disaster resilience capacity—from the causes of disaster losses and flood formation mechanisms. Furthermore, this paper constructs a flood disaster risk assessment model for Sichuan Province based on a cloud model, entropy value, and GIS technology. The model is validated by taking the July–August 2023 flood disaster as an example, and the results show that the distribution of the disaster was consistent with the flood risk assessment results of this paper, which verifies that the selected indicators are appropriate and the model is accurate and valid.

Construction Risk Assessment of Yellow River Bridges Based on Combined Empowerment Method and Two-Dimensional Cloud Model

(1) In recent years, the economy of the Yellow River basin in China has developed rapidly, and a series of large bridges across the Yellow River have been built on both sides of the Yellow River, which has brought great convenience to regional socio-economic activities. However, risk events are prone to occur during the construction of bridges across the Yellow River, which affect the safety of the bridges’ structure. Therefore, it is necessary to establish a new scientific risk assessment system for the construction safety of bridges across the Yellow River. (2) Methods: Firstly, based on the construction safety risk assessment index system of bridges across the Yellow River, the cloud AHP method and the cloud entropy weight method are used to determine the subjective weight and objective weight of risk indexes, and then the game theory combination weighting method is used to determine the comprehensive weight of each risk index, and then the digital characteristic values of the risk probability cloud and the consequence cloud are calculated and input into the forward cloud generator algorithm. MATLAB was used to generate a two-dimensional comprehensive cloud map, which was visually compared with the standard cloud map, and the probability level and consequence level of each risk index were preliminarily obtained. Finally, the risk assessment matrix was used for comprehensive risk evaluation. (3) Results: Applying the method to the construction safety risk assessment of the Jiaoping Expressway, the overall construction safety risk level of the Yellow River bridge was determined as level 4, and the risk levels of the four primary indicators were: personnel risk (level 3), material and equipment risk (level 4), construction technology risk (level 5), and construction environment risk (level 4). (4) Conclusions: The results of the risk evaluation are consistent with the actual construction state of the bridge, which shows that game theory’s combination of empowerment with a two-dimensional cloud model is scientific and effective when applied to the construction safety risk evaluation of Yellow River bridges.

Evaluating Expressway Safety Based on Fuzzy Comprehensive Evaluation with AHP–Entropy Method: A Case Study of Jinliwen Expressway in Zhejiang Province, China

To mitigate potential safety hazards during expressway operation, safety evaluation plays a crucial role. This study develops a fuzzy comprehensive evaluation model to assess the safety of expressway operations. First, an expressway operation safety risk assessment index system consisting of four criteria-layer indicators and 10 sub-criteria layer indicators is established. Then, the comprehensive weight of each evaluation index is calculated based on the combined AHP and entropy methods. Finally, the expressway safety level is obtained by converting qualitative indicators into fuzzy sets and defining corresponding membership functions to describe their degree of membership. The evaluation model is applied to the Jinliwen Expressway in a mountainous area in Zhejiang Province, China. The results show that the method could quantitatively and comprehensively evaluate the safety status of expressways and identify the weak links of operational safety management, which can effectively improve the safety level of expressway operations. The research findings will assist decision-makers in gaining a better understanding of the safety issues of expressways and, thus, using corresponding measures to enhance the safety level of the expressway.

Research on risk assessment method of subway driver driving fatigue based on AHP-FCE

Subway driver is one of the important factors in the "man-machine-environment" system of subway driving safety, which is of great significance to the safe operation of rail traffic. Based on the fatigue generation mechanism and previous experimental data, this paper establishes a risk assessment index system for subway driver driving fatigue including four elements: physiological, psychological, management and environmental factors based on systematic analysis of possible risks and influencing factors of driving fatigue. The Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) were organically combined to establish a driving fatigue risk assessment model for subway drivers and obtain the driving fatigue risk level of subway drivers. Finally, through the case evaluation of a single driver on the main line of an existing operation line, it is found that the risk level of driving fatigue of the subway driver is general risk, and the AHP-FCE model has good adaptability and rationality, which has good application value for the study of driving fatigue of subway drivers.

Risk Assessment and Response Strategy for Pig Epidemics in China.

Strengthening the analysis and risk assessment of the pig epidemic will help to better prevent and mitigate epidemic risks and promote the high-quality development of the pig industry. Based on a systematic understanding of live pig epidemics, a risk assessment index system was constructed, and the spatial and temporal variation characteristics of pig epidemics in China were explored by the entropy method. In recent years, the overall trend in pig epidemics over time first increased and then decreased; in space, the acceleration of the spread of epidemics across the country weakened. China still faces challenges, including many types and a wide range of diseases, large total livestock breeding and weak epidemic prevention and control capacity, and a large risk of introduced foreign animal epidemics. The spatial and temporal variations in the pig epidemic risk were obvious; one high-risk area, two medium-high-risk areas and 10 medium-risk areas have been found in recent years, during which time, the epidemic risk was highest in Beijing, Hainan, Liaoning, Tibet and Zhejiang. However, there were significant differences in the regional distribution of the risk level of pig epidemics in different years. To further build a secure "defense system" for the high-quality development of the pig industry, it is recommended to improve the monitoring and early warning system of pig epidemic risk, perfect the pig epidemic prevention and control system, and strengthen the regional collaboration mechanism of epidemic prevention and control.

Safety risk assessment of aircraft EWIS based on the improved combined weight and cloud model

Purpose This study aims to conduct the aircraft electrical wiring interconnection system (EWIS) safety risk assessment process abundantly and hierarchically and establish the assessment index system considering the weights and interrelationships of different levels of indices. Design/methodology/approach Due to the failure of EWIS being multifactorial, hidden and diverse, this paper divides the factors influencing the failure of EWIS into 3 primary indices, 13 secondary indices and 38 tertiary indices. Taking open circuit failure (OCF) and short circuit failure (SCF) as examples, calculate the weights of assessment indices based on the triangular fuzzy number analytic hierarchy process (TFNAHP) and triangular fuzzy number decision-making trial and evaluation laboratory (TFNDEMATEL). The cloud model (CM) divides the risk levels and obtains the safety risk assessment results. The comparative analyses of different weight calculation methods, different failure modes and different aircraft EWIS zones verify the effectiveness and practicability of the proposed method. Findings The results show that the proposed method aligns more with the actual situation than other methods. Also, the results identify key focus objects in EWIS safety risk assessment, such as the surrounding environmental factors among the primary indices having the most significant influence on OCF and SCF, the risk level of SCF being higher than that of OCF, etc. Originality/value This paper proposes a safety risk assessment index system for aircraft EWIS based on the cable parameters, surrounding environmental factors, installation and protection methods. The weight assignment is added to the assessment index system, and the safety risk assessment model is constructed by combining TFNAHP, TFNDEMATEL and CM.

A dynamic community gas risk-prediction method based on temporal knowledge graphs

This paper presents a community gas-safety risk-prediction method for solving the complex and continuous community gas-safety factors based on the temporal knowledge graphs. First, a community gas-safety risk-assessment index system is constructed based on the risk sources and factors influencing gas accidents. Entity and relationship features are extracted from the index system to construct a temporal knowledge graph of the community gas system. The community gas-safety risk-assessment index system is constructed based on the risk sources and risk-influencing factors of gas accidents. Furthermore, entity and relationship features are extracted in the index system to construct temporal knowledge graphs for a community gas system. Then, a gas-system risk-prediction method based on the temporal knowledge graphs is proposed, which predicts the risk level of the gas system in a certain period in the future. Finally, by applying the method in a specific community, the accuracy of the proposed prediction method is 74.87%, and the mean reciprocal rank is 87.44. The proposed gas-safety risk-prediction method based on a temporal knowledge graph network can assist managers in effectively managing community gas and has a positive auxiliary effect on sensing and controlling gas-safety situations.

Urban flood risk assessment characterizing the relationship among hazard, exposure, and vulnerability.

Risk assessment is an effective means to alleviate urban flood disasters and has attracted the attention of many studies. However, most previous studies about urban flood risk assessment often focused more on urban inundation area and depth, less on the inter-relationship of the components of risk. In this study, an urban flood risk assessment approach that characterizes the relationship among the three components of risk "hazard-exposure-vulnerability" (H-E-V) is developed. Firstly, eleven flood risk indicators are selected based on the flood simulation results of urban flood model and statistical data to establish the urban flood risk assessment index system. Then, the combination of analytic hierarchy process (AHP) and entropy weight method is employed to determine the weight of each indicator and the comprehensive urban flood risk is assessed. Most importantly, the coupling coordination degree model (CCDM) is used to reveal the relationship among H-E-V. After applying this method to Haikou city, China, the results show that the comprehensive effect and the coupling coordination degrees among H-E-V have a multidimensional impact on urban flood risk. For example, some sub-catchments, although at high risk of flooding, may experience a potential waste of resources. Urban flood assessment can be made more detailed and three-dimensional by comparing hazard, exposure, and vulnerability horizontally. Understanding and grasping the internal relationships among these three risk components can help implement flood prevention measures, optimize the allocation of flood prevention resources, and effectively reduce urban flood risks.

Risk assessment-based optimal safety measure for dust explosion in wooden products processing enterprises

A risk assessment method of dust explosion applicable to wood product processing enterprises was studied to effectively control the occurrence of dust explosion accidents. First, considering the explosive attributes of dust and the technical attributes of wood product processing, a risk assessment index system for dust explosion was constructed from the human, machine, environment, and management perspectives. It comprises 3 first-level indices (namely: accident possibility, accident severity, and safety management system), 6 second-level indices, and 28 third-level indices. The weight of each index was calculated using the structural entropy weight method (SEWM). Second, combined with an association degree matrix, a theoretical model for dust explosion risk assessment was established using a three-dimensional matrix method. Finally, an empirical analysis was conducted on a wood product processing plant using the established model. It was concluded that the overall risk level of the plant was level IV, indicating a relatively high risk. This conclusion is consistent with the actual operation status of the plant, showing that the model has a certain degree of applicability and effectiveness.

Improved PSS timing synchronization algorithm and IoT application in cross-border e-commerce risk identification

In this paper, a new timing synchronization algorithm for the main synchronous signal (PSS) is proposed for the risk identification of cross-border e-commerce in the Internet of things, aiming at the problems of poor performance of anti frequency bias and high computational complexity of the improved PSS timing synchronization algorithm. Based on the piecewise correlation algorithm, the normalized frequency deviation of PSS sequence is preset. The segmented ones are pre stored at the terminal by using the conjugate symmetry of PSS sequence. The fast correlation of each segment correlation window is realized by combining convolution and overlapping reservation block method. Then, the threshold judgment is made after the time delay accumulation of the correlation values of the segments is made, so as to complete the joint detection of timing synchronization and coarse frequency deviation. The simulation results show that the algorithm can improve the performance of the system anti frequency offset effectively, reduce the complexity of the calculation and show that the timing synchronization conditions of the Internet can be satisfied. At the same time, under the background of the current development of cross-border logistics, this paper reviews the current research status of Transnational E-commerce logistics and Transnational E-commerce logistics risk. By comparing the advantages and disadvantages of various risk assessment methods, neural network and genetic algorithm are selected as the basic risk assessment methods in this paper. Based on the improved PSS timing synchronization algorithm and the Internet of things, the risk indicators of e-commerce logistics transnational will be selected from five risk dimensions: platform risk, customs clearance risk, organizational risk, process risk and environmental risk. Through the comprehensive literature and expert’s opinion, the logistics risk assessment index system of cross-border e-commerce is established.

Toward ecological environmental risk for spoil ground group management in mega projects

PurposeThe numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.Design/methodology/approachBased on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.FindingsThe results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.Originality/valueThis paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

Risk Assessment of Scientific and Technological Cooperation among RCEP Countries Based on Cloud Model

Accurate risk assessment of international scientific and technological (S&T) cooperation is significant to international cooperation. In this paper, 5 risk dimensions with respect to the political, economic, social, cultural as well as technological of the regional comprehensive economic partnership countries (RCEP) are selected to establish a proper S&T cooperation index system for risk assessment. To calculate the weight of each index, a cross-entropy combination weighting method is proposed based on the combination weighting method of game theory. Furthermore, the standard cloud model is constructed by using the golden ratio, and the risk of S&T cooperation among the RCEP countries is analyzed by the cloud model. The results show that the combination weighting method proposed in this paper is effective, and its calculation is simpler than that of the game theory combination weighting method. Besides, compared with political, social, cultural, and technological indicators, economic indicators have a greater impact on S&T cooperation risk. Furthermore, it is also obtained from the results that the risk of S&T cooperation with China and the Philippines is at a lower to low level and medium to higher level, respectively, and the risk of S&T cooperation with other countries is all at a lower to medium level.

Prediction of Credit Card Loan Risk Based on Multilayer Perceptron Neural Network Model

Under the background of Internet finance and the popularization of intelligent terminal equipment, the scale of data and the diversity of information have developed exponentially rapidly, while the bad debt rate of personal credit is vague and much higher than that of commercial banks in the traditional technology period. Most of the traditional credit evaluation is driven by models, and the robustness of the risk control system is poor, which cannot meet the increasingly complex demand for default risk prediction. Since commercial banks have accumulated large-scale data assets, it has great significance to combine machine learning technology to help banks extract effective information from massive data and achieve risk assessment of borrowers, thereby reducing the risk of default in borrowing. This paper selects a credit card related data set, uses principal component analysis to extract feature vectors, and obtains a risk assessment index system for borrowers. Then, based on MLP neural network, a credit card loan risk prediction model is constructed. The study reads: The MLP model based on principal component analysis has high accuracy, fast running speed and strong stability. It is an ideal model for commercial banks to evaluate the credit risk of borrowers. This study can provide a new reference for commercial banks to solve the problem of credit risk prediction.