Risk Evaluation Indicator Research Articles

RETRACTED ARTICLE: Research and application of automatic monitoring system for tunnel-surrounding rock measurement based on GIS

This paper establishes a geological three-dimensional coordinate model and uses GIS to obtain the thickness of the overburden. The tunnel displacement monitoring points mainly include: vault settlement measurement points, foot settlement measurement points, and gap convergence measurement points. This paper constructs a GIS-based section tunnel entrance safety evaluation system, which provides a reference for the safety evaluation of the section tunnel entrance. The determination of the construction parameters and support parameters of the tunnel engineering is deeply affected by the stress conditions of the tunnel engineering. Under the conditions of limited economy and time, before tunnel construction, the mechanical parameters of the tunnel-surrounding rock are determined mainly through limited drilling. Although it is somewhat difficult, the construction parameters of tunnel engineering are also determined accordingly. The calculation results may cause the actual deformation of the surrounding rock to be quite different from the predicted deformation, and accidents may be caused according to the original construction plan. Therefore, the supervision and measurement of tunnel engineering is particularly important. At the same time, a risk evaluation system is established to achieve the control of risk evaluation indicators, which can intuitively express the size of the tunnel entrance affected by the evaluation factors, calculate the mechanical parameters of the surrounding rock of the tunnel, determine the construction parameters and support parameters of the tunnel project, and analyze the measured displacement changes to ensure long-term stable construction and support. Through the actual application of the project, it can be seen that the risk assessment system can also conveniently and quickly query and analyze the monitoring data of the tunnel, and it can realize online operation and analyze the stability of the same surrounding rock. This proves the rationality of the planning and framework of the detection system, and it has high application value.

A New Quantitative Method for Risk Assessment of Coal Floor Water Inrush Based on PSR Theory and Extension Cloud Model

In order to scientifically and reasonably assess the risk of water inrush from the coal seam floor, considering the influence of natural environmental factors such as hydrogeology, mining, and human intervention, the PSR model of ecosystem health evaluation was introduced, and the risk evaluation indicator system of water inrush from the coal seam floor was established. In order to solve the randomness and fuzziness of water inrush event evaluation, the evaluation model is constructed based on extension cloud theory and is applied in the 12123 working face of Pan Er coal mine of Huainan Mining Group. The application results show that the evaluation results are basically consistent with the actual situation, which shows that the model can be used in the actual evaluation work and is scientific.

Risk evaluation of tailings dam-break based on the extension matter-element model

As one of the most concerned risk sources of mining enterprises, the safety and stability of the tailings storage facility (TSF) is closely connected to the operating activity, surrounding ecological environment, and residents' lives safety and properties safety. In order to evaluate the risk of the tailings dam break, the extension matter-element model has been applied in the work. First, the risk evaluation indicator system was established, included 3 levels, 4 criteria and 17 individual indicators. Next, the weight of each indicator was computed by using the analytic hierarchy process (AHP) method. Then, the classical field, controlled field and closeness function within the extension matter-element model were determined considering the TSF height and volume, and the principle of the maximum membership degree has been improved by the closeness. Finally, a case study was illustrated to demonstrate the effectiveness of the model. The result indicated that the target TSF operated at a relatively lower risk level, which accurately reflected the real operating situation. This work can provide a reasonable reference for dam break risk evaluation.

Multi-dimensional risk assessment of electricity market based on cloud model

Aiming at various potential risks in the electricity market, this paper establishes a risk assessment index system for the electricity market from four dimensions of structural risk, operation risk, fairness risk, and behavioral risk. The analytic hierarchy process is used to determine the subjective weight of risk evaluation indicators, and the entropy method is used to determine the objective Weight, according to the least squares optimization idea to get the comprehensive weight. Then, the basic theory and calculation method of cloud model are introduced, and the standard cloud of risk level evaluation is constructed. Finally, the analysis of a calculation example shows that the risk evaluation level of the selected regional electricity market is moderate, which verifies the validity and feasibility of the model proposed.

Research on the application of enterprise credit supervision risk evaluation index based on fuzzy matter-element of comprehensive evaluation

Credit supervision is not only an important institutional arrangement for the construction of social credit system, but also one of the main ways to give full play to the value and role of credit. The risk evaluation of enterprise credit supervision can provide important reference for classified supervision. The research on the risk evaluation model and indicators of enterprise credit supervision is of great significance to improve the scientificity and accuracy of enterprise credit supervision risk evaluation. Through the research and analysis of enterprise credit supervision risk evaluation model and evaluation index, the fuzzy matter-element evaluation model is constructed, and the comprehensive weight of enterprise credit supervision risk evaluation index is calculated by subjective and objective weighting methods respectively, and the main factors affecting the level of enterprise credit supervision risk are analyzed, so as to provide suggestions for enterprises to carry out credit supervision risk evaluation and strengthen credit supervision risk management It provides a scientific reference.

Risk Assessment of aGas Well Test in the South China SeaBased on Fault Tree Analysis

Deepwater gas well testing in the South China Sea is characterized by high difficulty, high investment and high risk. In order to reduce effectively the risk of the gas well testing operation in the South China Sea, the potential risk factors in the South China Sea deepwater testing operation were analyzed and 42 categories of risk factors were identified. The fault tree analysis method was used to establish the fault tree model for a deepwater testing operation in a South China Sea gas well, and analyze the inter restricted relationship between risks. Combining with the hierarchical analysis method to calculate the weight values of the risk evaluation indicators and use the product of it with probability importance as the corrected value for the probability of occurrence of the basic event in the fault tree model, the fault tree analysis was performed to determine the probability of occurrence of the top-level event. The results of the study help reduce the risk of accidents in deepwater gas well testing operations and can inform the management of deepwater gas well testing sites.

Research on PC Component Quality Risk Evaluation Based on Intuitionistic Fuzzy Analytic Hierarchy Process

In order to further promote the development of prefabricated buildings, enrich the theoretical knowledge of the quality risk research of concrete prefabricated components, from the perspective of total quality management, the risk factors are divided into 5 aspects: personnel, equipment, system schemes, environment and raw material factors. With indicators and related descriptions, a set of risk evaluation indicator system is established. Based on the intuitionistic fuzzy analytic hierarchy process, the index weights of various risk factors are calculated, and a comprehensive quality risk evaluation model is established. The effectiveness of the model is proved by an example analysis, and the corresponding quality control points are summarized, with a view to the quality management provides a reference.

Risk Assessment of Seaplane Operation Safety Using Bayesian Network

Seaplanes have become popular tourism and transportation tools with the ability of take-off and land on water. Recent seaplane accidents are highlighting the need for safety analysis of the seaplane operation process, which includes the sequential stages of water-taxiing, take-off, flight, and landing. This paper proposes a novel approach to modeling the risk of seaplane operation safety using a Bayesian network (BN). The rough risk factors that may cause seaplane accidents are identified by historical data, literature review, and interviews with experts. Based on the identification result, a risk evaluation indicator system is constructed and screened by the Delphi method. The structure of the proposed BN is derived from the indicator system. The parameter of the BN is obtained by expert experience and parameter learning from statistical data. The BN model is validated with an out-of-sample test demonstrating nearly 95% prediction accuracy of the accident severity level. The model is then applied to conduct diagnosis inference and sensitivity analysis to identify the key risk factors for seaplane operation accidents. The result shows that the four most critical risk factors are mental barrier, mechanical failure, visibility, and improper emergency disposal. It provides an early warning to take appropriate preventive and mitigative measures to enhance the overall safety of the seaplane operation process.

Modeling Lane-Change Risk in Urban Expressway Off-Ramp Area Based on Naturalistic Driving Data

Abstract Off-ramp areas are considered the critical sections of urban expressways where the exiting vehicles and straight-through vehicles merge. Therefore, lane-change behaviors frequently occur at the upstream of the urban expressway off-ramp, which lead to high chance of traffic crashes. This study looks at the risk of lane-change behaviors in the multilane urban expressway off-ramp areas. First, lane-change process information of exit vehicles in urban expressway off-ramp area was extracted from the Shanghai Naturalistic Driving Study (SH-NDS) database. Second, for each lane-change movements of exit vehicles, a risk evaluation indicator (risk perception, RP) was adopted to quantify the lane-change risk. Based on the RP, the study proposed a four-rank risk classification criterion using K-means clustering to define the risk rank of each lane-change movement. Finally, a lane-change risk rank classification model was developed for traffic in the off-ramp areas of multilane expressways using four distinctive influencing factors. Four influencing factors, namely, traffic congestion level, demand lane change times, lane-change direction, and relative distance between vehicle and exit, were used to describe the traffic flow characteristics and exiting lane-change route for the modeling purpose. The risk model was developed using two support vector machine models, which were based on the partial binary tree structure and the directed acyclic graph structure, respectively. The results showed that the overall accuracy of the partial binary tree structure classifier was 65.71 % and the average AUC value was 0.9004, both of which shows a better performance of the partial binary tree structure classifier, compared with the directed acyclic graph structure classifier.

How to allocate energy-saving benefit for guaranteed savings EPC projects? A case of China

From the perspective of stakeholders, this paper uses Shapley value method to get the initial allocation solution to energy-saving benefit of guaranteed savings energy performance contracting (EPC) project, and uses AHP to determine the risk evaluation indicators and the weight of stakeholders. The fuzzy comprehensive evaluation method is used to determine the risk coefficients of stakeholders and normalize them. The initial allocation of energy-saving benefit is corrected by using the normalized risk coefficients to get the final allocation solution to the energy-saving benefit. The study shows that (1) It is reasonable to use the Shapley value method for the allocation of energy-saving benefit of stakeholders in guaranteed savings EPC projects; (2) In the process of forming a cooperative alliance among stakeholders of guaranteed savings EPC projects, all parties have synergistic risks; (3) The level of energy-saving benefits of the cooperative alliance has been improved. (4) The allocation of energy-saving benefit based on risk coefficient is more in line with the actual situation. The research results can provide a more realistic allocation solution to energy-saving benefits of such projects, and contribute to the smooth implementation of guaranteed savings EPC projects that occupy the mainstream position in China’s energy-saving service industry.

Research on Chongqing Mountain Flood Disaster Risk Assessment System Based on AHP-GIS

The risk of mountain flood disasters is the fundamental factor restricting the occurrence of disasters. The analysis and assessment of disaster risks is the basis for disaster risk management. Through the investigation of mountain flood disasters from 2013 to 2015, the basic information such as hydrometeorology, topography, socio-economic and mountain flood disaster prevention and control situation in mountain flood disaster prevention and control areas were found out. Taking the city of mountains-Chongqing as an ex-ample, this paper considered the results of mountain flood disaster investigation and evaluation in recent years, and divided the risk evaluation indicators into two types of first-level indicators: rainfall and under-lying surface, and the secondary indicators were subdivided into comprehensive rainstorm indicators, critical rainfall, topographic relief, land use convergence capacity, soil texture and river network density. Using AHP to set the weight coefficient of each level indicators, those showed that heavy rain conditions, critical rainfall and topographic relief were important factors impacting the mountain flood disasters, and the land use convergence capacity had the minimum weight coefficient. Through GIS superposition analysis, the risk index of mountain flood disasters in the region were obtained. The western, southeastern and northeastern Chongqing were high risk areas for mountain flood disasters, which provided decision-making basis for mountain flood disaster risk management.

Risk Evaluation Model of Life Loss Caused by Dam-Break Flood and Its Application

The internal mechanism affecting life loss caused by a dam-break flood is complicated. On the basis of analyzing the risk formation path, a risk evaluation indicator system was established which included the hazards, exposure and vulnerability factors. Variable Fuzzy Sets theory was introduced into the risk evaluation of life loss risk grades and applied to eight collapsed dams in China. According to the sequence of the risk grades of these dams, the evaluation result was mainly consistent with the actual mortality ranking sequence, showing that the model could be effectively applied to the risk evaluation of life loss in dam-break events. Aimed at the problem of large differences in the downstream population distribution of dams in China, this manuscript suggested that 10,000 people should be the basis for the grouping operation of dams in the risk evaluation. These Variable Fuzzy evaluation models and grouping suggestions could help stakeholders to allocate the funds for dam reinforcement more accurately and provide a scientific basis for the study of dam-break life loss and dam risk management.

Research on Risk Management of Fresh Agricultural Products Supply Chain Based on Fuzzy Analytic Hierarchy Process

There's a great improvement in people's requirements for food quality under the development of the economy, which leads to the nutrition and health of fresh agricultural products more and more loved by people. However, the characteristics of fresh produce itself, the inevitable high requirements for the surrounding environment and logistics level, and the unpredictable environment and relatively backward logistics development level inevitably increase the risks of the supply chain, the risk of fresh produce determines the need for research by practitioners and researchers concerned with fresh produce. This paper uses fuzzy analytic hierarchy process to analyze the risks in the fresh agricultural product supply chain, and summarizes the four models of China's fresh agricultural product supply chain enterprises, supermarket chains, wholesale markets, and fresh electronic business. There are six categories: production risk, demand risk, supply risk, cooperation risk, logistics risk, and environmental risk, thus establishing a risk evaluation indicator system. It is expected to put forward the risk management strategy to promote the supply chain development of fresh agricultural products.

A Method to Build a Risk Evaluation Weighted Indicators System and an Application Example in Online Shopping Risk Evaluation

FMEA (Failure Mode and Effects Analysis) is widely used to evaluate risks and the measurement in complex projects during design stage. But for some cases where the decision is not so complex, a simple result of risk evaluation such as a comprehensive score is more helpful, e.g. when evaluating and comparing the online shopping risks related to different retailers to help the consumers make choice, it’s better to provide a comparable trustfulness score with every retailer. Though such cases are common, seldom research has been focused on them. One convenient and common method is to design a risk evaluation system including several weighted indicators and the rating standards for every indicator, by which it’s much easier to repeat the process to evaluate many objects. In this article, one method to build a risk evaluation indicators system that guarantees the proportional relationship between the resulting score and the expected risk loss is proposed and is adopted in online retailing trustfulness evaluation as an application example.

Quality Risk Evaluation of the Food Supply Chain Using a Fuzzy Comprehensive Evaluation Model and Failure Mode, Effects, and Criticality Analysis

Evaluating the quality risk level in the food supply chain can reduce quality information asymmetry and food quality incidents and promote nationally integrated regulations for food quality. In order to evaluate it, a quality risk evaluation indicator system for the food supply chain is constructed based on an extensive literature review in this paper. Furthermore, a mathematical model based on the fuzzy comprehensive evaluation model (FCEM) and failure mode, effects, and criticality analysis (FMECA) for evaluating the quality risk level in the food supply chain is developed. A computational experiment aimed at verifying the effectiveness and feasibility of this proposed model is conducted on the basis of a questionnaire survey. The results suggest that this model can be used as a general guideline to assess the quality risk level in the food supply chain and achieve the most important objective of providing a reference for the public and private sectors when making decisions on food quality management.

Comprehensive evaluation of the potential risk from cyanobacteria blooms in Poyang Lake based on nutrient zoning

The potential risk from cyanobacteria blooms is the basis for predicting, preventing, and managing eutrophication. Poyang Lake lies on the southern bank of the middle and lower reaches of the Yangtze River. This lake is a large shallow lake connected to the Yangtze River and is affected by monsoon. The comprehensive evaluation index system, evaluation model, and method of the potential risk from cyanobacteria blooms were constructed based on the nutrient zoning in Poyang Lake, and the potential risk from cyanobacteria blooms was evaluated in 2013. (1) The evaluation index system comprises physical, chemical, and biological indicators. The physical indicators consist of blocking degree, lake region location, transparency (Secchi disk depth, SD), and temperature; the chemical indicators consist of total nitrogen (TN) and total phosphorus (TP); and the biological indicators consist of chlorophyll a (Chla) and phytoplankton biomass. Among the indicators, blocking degree and lake region location along with the prevailing wind direction were selected to represent the indicators affected by water retention time and wind direction. (2) We established a comprehensive evaluation method for assessing the potential risk from cyanobacteria blooms by adopting both analytic hierarchy process weighting and a comprehensive evaluation method. (3) Results show that the high-risk periods for cyanobacteria blooms were August, July, and December, and the high-risk regions were in the Northeastern Lake Region, Western Lake Region and Northern Lake Region. The Northeastern Lake Region is particularly in high risk in August and July. These cyanobacteria blooms presented heavy risk or close to heavy risk. Based on the risk evaluation indicators, outbreaks of cyanobacteria blooms are limited by temperature and location. Chla and phytoplankton biomass were the key indices affecting the level of potential risk from cyanobacteria blooms during the high-water-level period (July and August). In contrast, TN and TP are the key indices affecting the level of harm during the low-water-level period. Within a year, Chla, phytoplankton biomass, and TP are key indicators for the prediction of cyanobacteria blooms in Poyang Lake.

Landing Risk Assessment of Carrier-Based Aircraft Based on Fuzzy Multi-Attribute Group Decision Making

In allusion to the special characteristic of longitudinal loop risk assessment in landing process of carrier-based aircraft, this paper extends the concept of decision-maker, and proposes a method of fuzzy multi-attribute decision making with normal fuzzy linguistic variables as decision-making information. Based on the establishment of carrier-based aircraft landing model, the expressions of risk evaluation indicators are ensured, and the relative attribute weight is calculated by the simulation of the safe flight area in landing process. The application of risk assessment is implemented by analogy between standard points and decision-maker. The analysis of numerical examples shows that the method is practical and the application in risk evaluation is reasonable. Multipoint decision information is complete and decision results accord with distributions of touchdown points. Comprehensive evaluation of flight safety with different pilots can be realized.

Reduction of Risk Control Indicators of ERP System Based on Rough Set

the risk evaluation indicator system by enterprise resource planning (ERP) system is characterized by excessive subjectivity, lack of reasonable basis for establishing, and redundancy. The paper adopts the rough set theory, proposes attribute reduction algorithm based on information entropy, and makes attribute reduction on risk control indicators for implementation of ERP system by integrating cases from 10 enterprises that have already implemented ERP systems. The resultsshow that attribute reduction algorithm based on rough set is effective and available on reduction of risk control indicator for implementation of ERP system.

A HYBRID MULTIPLE CRITERIA DECISION-MAKING MODEL FOR INVESTMENT DECISION MAKING

Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios.

Research on Risk of Automotive Product Life Cycle Design Based on Low Carbon Requirements

Based on low-carbon and product life-cycle design concept, this paper classifies risk factors in different stages of automotive product life cycle design risk evaluation indicator system and analyzes the different risk categories weight adopting the rough set and analytical hierarchy process to determine the key risks of automotive product in different stages of life cycle. Additionally, real instances are cited to verify the conclusions.