Variable Fuzzy Set Research Articles

Quantitative Identification of the Water Resistance Capacity of Composite Strata in Mining Coal Seam Floors

In coal seam mining, the water resistance of the floor composite strata is the key to determining whether water disaster occurs or not and to formulating water control countermeasures. Taking the Pingdingshan Coalfield No. 8 mine and Shoushan mine as the research objects, the thickness ratio of plastic brittle rock, core recovery rate, thickness of effective aquiclude, fault complexity, composite compressive strength, and equivalent water resistance coefficient were selected as the index factors. The comprehensive weight of each index factor was determined by using the entropy weight theory. The water resistance of the J16-17 coal seam floor composite rock in the study area was quantitatively evaluated using the fuzzy variable set mathematical model and was divided into five grades: extremely weak, weak, medium, strong, and very strong. The results show that the J16-17 coal floor composite rock layers with strong and very strong water resistance areas account for 23.64% of the total area, the medium areas account for 58.26%, and the weak and extremely weak areas account for 18.1%. These results provide support for the accurate assessment of water inrush hazards of a coal floor.

Mitigation of stretch type vampire attack using probabilistic variable fuzzy rough set in wireless sensor networks

AbstractEnergy consumptions of intermediate nodes play an anchor role in achieving maximum cooperation for reliable dissemination of data in wireless sensor network (WSNs). WSN is considered a highly challenging issue due to its ad hoc node's organization in the network. In specific, vampire attack weakens the sensor nodes by draining energy slowly resulting in network performance deterioration ending up in network failure. The vampire attack needs to be detected and isolated for improving the sensor nodes life span to the maximum extent. In this article, mitigation of stretch type vampire attack using probabilistic variable fuzzy rough set (MVA‐PVFRS) is proposed with the merits of fuzzy membership ranks to sustain network lifetime. This MVA‐PVFRS scheme derives the benefits of fuzzy information system by including the method of approximation concept that decides upon the mitigation of vampire nodes through the formulation of lower and upper cooperation thresholds. Furthermore, it is proposed to handle the degree of uncertainty, missingness, and vagueness of data disseminated between the sensor nodes during the monitoring process in the network. The simulation results of the proposed MVA‐PVFRS scheme is attained through ns‐2 simulations with different number of sensor nodes, number of vampire nodes, pause time of simulation, number of packets, and packet sizes. The results of the proposed MVA‐PVFRS scheme with the different number of packets confirmed an excellent performance in packet delivery rate by 15.84% and throughput by 16.94%, compared to the baseline schemes.

An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem.

Exploring efficiency approaches to solve the problems of decision making under uncertainty is a mainstream direction. This article explores the rough approximation of the uncertainty information with Pythagorean fuzzy information on multi-granularity space over two universes combined with grey relational analysis. Based on grey relational analysis, we present a new approach to calculate the relative degree or the attribute weight with Pythagorean fuzzy set and give a new descriptions for membership degree and non-membership. Then, this paper proposes a multi-granulation rough sets combined with Pythagorean fuzzy set, including optimistic multi-granulation Pythagorean fuzzy rough set, pessimistic multi-granulation Pythagorean fuzzy rough set and variable precision Pythagorean fuzzy rough set. Several basic properties for the established models are investigated in detail. Meanwhile, we present an approach to solving the multiple-criteria group decision making problems with fuzzy information based on the proposed model. Eventually, a case study of psychological evaluation of health care workers in COVID-19 show the principle of the established model and is utilized to verify the availability. The main contributions have three aspects. The first contribution of an approach of calculating the attribute weight is presented based on Grey Relational Analysis and gives a new perspective for the Pythagorean fuzzy set. Then, this paper proposes a mutli-granulation rough set model with Pythagorean fuzzy set over two universes. Finally, we apply the proposed model to solving the psychological evaluation problems.

Quantitative evaluation of sustainable development ability of deep buried geothermal water coupled with key index factors

ABSTRACT Scientific evaluations of the sustainable development ability of deep-buried geothermal water are essential to fully utilizing these resources while simultaneously minimizing negative environmental effects. However, due to the multi-source and variability of accumulated information in the process of geothermal water development, the precise identification of spatial differences in sustainable development capabilities is still in the exploratory stage. Taking geothermal water of thermal reservoirs with buried depths of 1000–1200 m and 1200–1400 m of downtown Kaifeng City China as an example, the exploitation potential, well distribution density, geothermal gradient, water level decline rate, recharge volume, and specific yield are selected as index factors. The weights of index factors are determined based on the gray correlation analysis method, and the sustainable development ability of the geothermal water is quantitatively evaluated using fuzzy variable set theory. Our research shows that the geothermal water resources of the 1000–1200 m deep thermal reservoir in Kaifeng can be divided into three sustainable development ability zones: ‘weakest’, ‘medium’, and ‘strong’. Moreover, the 1200–1400 m deep thermal reservoir can also be divided into three sustainable development ability zones: ‘weakest’, ‘weak’, and ‘strongest’. This research work provides a direction for the rational development and scientific protection of geothermal water.

The Decision of an Eco-Friendly Reservoir Operation Scheme Based on a Variable Set

The river ecosystem has the characteristics of the coexistence of clarity and ambiguity. The starting point of eco-friendly reservoir operation is to fully consider the ecological water requirements of the lower reaches of the reservoir, so it also has the characteristics of clarity and vagueness. The fuzzy theory is an excellent tool to realize the quantification of fuzzy concepts. In this paper, the variable set theory (VS) is introduced into the decision-making field of eco-friendly reservoir scheduling scheme optimization. Taking Ertan Hydropower Station as an example, the scheduling scheme optimization is carried out. To verify the effectiveness of the evaluation method, this paper compares and analyzes the evaluation results of the fuzzy set evaluation method and the composite fuzzy matter-element method. The results show that the variable fuzzy set method has the advantages of rigorous theory, a concise model, and simple calculation, and the decision result is reasonable and reliable. This research can provide new ideas for the decision-making research of engineering.

Using Improved SPA and ICS-LSSVM for Sustainability Assessment of PV Industry along the Belt and Road

Scientific and timely sustainability evaluation of the photovoltaic industry along the Belt and Road is of great significance. In this paper, a novel hybrid evaluation model is proposed for accurate and real-time assessment that integrates modified set pair analysis with least squares support vector machine that combines improved cuckoo search algorithm. First, the indicator system is set from five principles, namely economy, politics, society, ecological environment and resources. Then, the traditional approach is established through modifying set pair analysis on the basis of variable fuzzy set coupling evaluation theory. A modern intelligent assessment model is designed that integrates improved cuckoo search algorithm and least squares support vector machine where the concept of random weight is introduced in improved cuckoo search algorithm. In the case analysis, the relative errors calculated by the proposed model all fluctuate in the range of [−3%, 3%], indicating that it has the strongest fitting and learning ability. The empirical analysis verifies the scientificity and precision of the method and points out influencing factors. It provides a new idea for rapid and effective assessment of PV industry along the Belt and Road, as well as assistance for the sustainable development of this industry. This paper innovatively proposes the sustainability evaluation index system and evaluation model for the photovoltaic industry in countries along the Belt and Road, thus contributing to the promotion of sustainable development of the photovoltaic industry in countries along the Belt and Road.

Sustainable Development Evaluation of Innovation and Entrepreneurship Education of Clean Energy Major in Colleges and Universities Based on SPA-VFS and GRNN Optimized by Chaos Bat Algorithm

The research on the sustainability evaluation of innovation and entrepreneurship education for clean energy majors in colleges and universities can not only cultivate more and better innovative and entrepreneurial talents for the development of sustainable energy but also provide a reference for the sustainable development of innovation and entrepreneurship education for other majors. To achieve systematic and comprehensive scientific evaluation, this paper proposes an evaluation model based on SPA-VFS and Chaos bat algorithm to optimize GRNN. Firstly, the sustainability evaluation index system of innovation and entrepreneurship education for clean energy major in colleges and universities is constructed from the four aspects of the environment, investment, process, and results, and the meaning of each evaluation index is explained; Then, combined with variable fuzzy set evaluation theory (VFS) and set pair analysis theory (SPA), the classical evaluation model based on SPA-VFS is constructed, and the entropy weight method and rank method are coupled to obtain the index weight. The basic bat algorithm is improved by using Tent chaotic mapping, and the chaotic bat algorithm (CBA) is proposed. The generalized regression neural network (GRNN) model is optimized by CBA, and the intelligent evaluation model based on CBA-GRNN is obtained to realize fast real-time calculation; finally, a numerical example is used to verify the scientificity and accuracy of the model proposed in this paper. This study is conducive to a comprehensive evaluation of the sustainability of innovation and entrepreneurship education for clean energy major in colleges and universities, and is conducive to the healthy and sustainable development of innovation and entrepreneurship education for clean energy major in colleges and universities, so as to provide more innovative and entrepreneurial talents for the clean energy industry.

Grey variable dual precision rough set model and its application

PurposeThe purpose of this paper is to advance a novel grey variable dual precision rough set model for grey concept.Design/methodology/approachTo obtain the approximation of a grey object, the authors first define the concepts of grey rough membership degree and grey degree of approximation on the basic thinking logic of variable precision rough set. Based on grey rough membership degree and grey degree of approximation, the authors proposed a grey variable dual precision rough set model. It uses a clear knowledge concept to approximate a grey concept, and the output result is also a clear concept.FindingsThe result demonstrates that the proposed model may be closer to the actual decision-making situation, can effectively improve the rationality and scientificity of the approximation and reduce the risk of decision-making. It can effectively achieve the whitenization of grey objects. The model can be degenerated to traditional variable precision rough fuzzy set model, variable precision rough set model and classic Pawlak rough set, when some specific conditions are met.Practical implicationsThe method exposed in the paper can be used to solve multi-criteria decision problems with grey decision objects and provide a decision rule. It can also help us better realize knowledge discovery and attribute reduction. It can effectively achieve the whitenization of grey object.Originality/valueThis method proposed in this paper implements a rough approximation of grey decision object and obtains low-risk probabilistic decision rule. It can effectively achieve a certain degree of whitenization of some grey objects.

VFS-based OFSP model for groundwater pollution study of domestic waste landfill.

The groundwater quality is essential for high quality of life and social development. Thus, the importance and necessity of the accurate and rigorous requirements for contaminated groundwater assessment has increasingly attracted engineers' and researchers' attentions. In order to improve the precision and robustness of the groundwater quality evaluation of domestic waste landfills, based on the variable fuzzy set (VFS) pair and the optimized N.L. Nemerow index, we develop an optimized fuzzy set pair (OFSP) model for groundwater quality assessment. Then, we devise the OFSP model by five key elements of optimized synthesis operator "C", relative difference[Formula: see text], connection degree"ui", optimized N.L. Nemerow index "Pi," and pollution load ratio "Ji", which can achieve the reasonable groundwater quality assessment model, the stable groundwater quality evaluation process, and the convincing evaluation results. Finally, a case study on groundwater quality assessment of various domestic landfills in China is conducted to explore the comprehensive impacts of domestic landfills in different regions and types on groundwater pollution from multiple perspectives, and demonstrate the effectiveness of the proposed OFSP model. The groundwater quality assessment results of various domestic landfills indicate that the pollution level of groundwater under unregulated domestic landfills in eastern and southern China is the worst. Based on the assessment results of groundwater quality, we compare the groundwater quality levels obtained by various mainstream methods. In line with precision (0.985), correlation (0.934), robustness (0.953), and rationality (0.946), our designed OFSP model has the best performance. In addition, according to the indexes of discrimination (0.217) and versatility (0.837), the designed OFSP model also has a good ability. Results of experiments well prove that the proposed OFSP model could play a good performance on groundwater quality evaluation in domestic landfills, compared with other mainstream models.

A novel comprehensive model of set pair analysis with extenics for river health evaluation and prediction of semi-arid basin - A case study of Wei River Basin, China

The accelerated development of urbanization in semi-arid areas is easy to cause varying degrees of disturbance to its fragile aquatic ecosystem. To find a general method for assessing the health status in semi-arid basins in China, and to provide theoretical basis for river health management and sustainable development, this study is that health evaluation index system is established in the Wei River Basin, covering a huge semi-arid area, and analyzed the biological structure of plankton obtained by field sampling and identified in laboratory, chemical conditions including dissolved oxygen, water temperature, ammonia nitrogen, pH, chlorophyll and other water physical and chemical factors determined by field instruments and sediment heavy metals analyzed in laboratory, physical habitat scored on site and social factors including water resource utilization rate and water consumption per 10,000 yuan of GDP collected in local water resource bulletin. Based on the idea of game theory, an improved coupling model of set pair analysis with extenics is established to assess and predict health. The results show that Wei River System and Jing River System are healthy, Beiluo River System is sub-healthy, and the whole Wei River Basin is also healthy; most of the cross-sections have a tendency to change to a bad level. Compared with simple weighting, set pair analysis and variable fuzzy set methods based on the corresponding sampling data and the weight in this paper, the coupling model can explain the transition and its trend between levels, reflect the certainty and uncertainty, and get more accurate results. It is suggested that daily monitoring and management should be strengthened in most sections to improve their health. And improve the development level of ecological function and social service function, give priority to the development of downstream water resources economy.

Evaluation of groundwater quality using an integrated approach of set pair analysis and variable fuzzy improved model with binary semantic analysis: A case study in Jiaokou Irrigation District, east of Guanzhong Basin, China

The study proposes a new set pair analysis - variable fuzzy improved model (SPA-VFIM) by integrating the set pair analysis (SPA), variable fuzzy sets (VFS) theory, and binary semantic (BS). The SPA-VFIM method gets over the shortcomings of the existing SPA and VFS methods. The use of BS solves the problem of the weighted average principle (WAP) not being conducive to the timeliness of assessment. The existing and newly proposed methods were used to evaluate the groundwater quality in the Jiaokou Irrigation District, China, to show the advantages of the SPA-VFIM method. The results of SPA-VFIM method show that more than 80% of the groundwater, mainly distributed in the central and western parts of the study region, is assessed as level IV and level V, according to the Chinese Groundwater Quality Standards (GB/T 14848-2017). The assessment results are consistent with ground-based measurements of water quality, and NO3−, Na+, SO42−, Total Hardness (TH), and Cl− are the main pollutants. The SPA-VFIM and existing methods were compared. The results indicate that 57.69% and 76.92% of the assessment results by the SPA-VFIM method agree well with that of the SPA and VFS methods, respectively, indicating that the new SPA-VFIM method is reasonable and effective in groundwater quality. The results of groundwater quality assessment show that local authorities should pay more attention to areas with poor and very poor groundwater quality. These findings are beneficial to the future groundwater management plans dealing with drinking and irrigation and the sustainable development of water resources in this irrigation district.

Spatiotemporal changes caused by the intensive use of sea areas in the liaoning coastal economic zone of China.

Oceans and their resources are experiencing immense pressure because of human exploitation. The intensive use of sea areas has become an important method in solving the contradiction between ocean supply and demand, thereby ensuring sustainable marine economy development, tapping potential sea-area utilization, reasonably allocating sea-area utilization structures, and increasing marine economic benefits. This paper explores the definition and connotation of intensive sea-area use and constructs an evaluation index system based on marine input intensity, marine utilization structure, marine economic benefit, and marine ecological environment. Multi-objective variable fuzzy set theory and fuzzy decision analysis methods were used to evaluate the intensive sea-area utilization in the Liaoning Coastal Economic Zone of China during 2004–2016. The spatial differentiation characteristics of intensive sea-area use were analysed using cluster analysis. The research result showed that: (1) Intensive utilization level of the Liaoning coastal economic zone has gradually increased, while it is still in a moderately weak level; (2) Sea area intensive utilization varied in degrees and fluctuates in the six cities under the jurisdiction of the Liaoning coastal economic zone; and (3) Marine input intensity, marine utilization structure, marine economic benefit, and marine sustainability indexes have increased in the cities, thereby exhibiting improvements in the Liaoning coastal economic zone.

Quantitative Evaluation for the Threat Degree of a Thermal Reservoir to Deep Coal Mining

Taking the Suiqi coalfield located in North China as the object, where the coal seam burial depth is more than 1100 m, the water abundance of the roof pore thermal storage aquifer is better than average, the ground temperature is abnormally high, and hydrogeological data are relatively lacking, this paper selects and determines eight index factors that influence the mining of the coalfield. Based on the analytic hierarchy process (AHP), the index factor weight is defined, and then, the threat degree of the roof thermal storage aquifer to the coal mining is quantitatively evaluated and divided by using the fuzzy variable set theory. The evaluation results show that the threat degree of the roof in the eastern region is generally greater than that in the western region and that the closer it is to the coal seam outcrop line, the higher the threat degree is; near the boreholes, in the areas Qs1,Qs5, Qs8, Sx1, Tk5, Zc4, and Zc7, which are close to the hidden outcrop line of the coal seam, the classification characteristic value of the threat degree is greater than 3.5, which is in the high-threat zone for disasters caused by roof thermal storage aquifers during coal seam mining. The area above the medium-threat zone accounts for 71.82% of the total study area, indicating that deep coal mining is affected by multiple factors and that roof water and heat disasters are more likely to occur.

Evaluation on sustainable utilization of water resources in Nansi Lake Basin

Based on the influencing factors of sustainable development by Bossel, the evaluation index system of sustainable utilization of water resources was constructed, which includes 18 indexes considering the development and utilization of water resources, social economy and ecological environment. The evaluation grade was classified into five levels: special, strong, intermediate, light and tiny. Because there were many fuzzy characteristics in this evaluation, this study was constructed an evaluation method of sustainable utilization of water resources based on the variable fuzzy sets model. Taking the Nansi Lake Basin in China as an example, the evaluation method was introduced in detail. The example showed that the evaluation index system constructed in this paper was reasonable and generalized, and the evaluation method was easy to understand, easy to operate and high credibility of the results. In addition, the evaluation results had a certain guiding significance for the sustainable development of water resources.

Using Multiple Index Comprehensive Method to Assess Urban Rainstorm Disaster Risk in Jiangsu Province, China

An integrated index system for urban rainstorm risk evaluation has been developed. Meanwhile, an information diffusion method (IDM) and variable fuzzy sets (VFSs) were employed to evaluate the dangerousness, sensitivity, and vulnerability risk of urban rainstorm disasters, respectively. Then, the comprehensive risk zoning map was drawn. Finally, Jiangsu Province has been taken as a case study area. Due to heavy rainfall in short-term and low rainstorm resistance ability, Wuxi, Changzhou, Nanjing, and Suzhou have higher dangerousness while Wuxi, Changzhou, and Nanjing have higher sensitivity. And because of potential losses in urban rainstorm disaster, Wuxi and Suzhou have higher vulnerability than other cities. The comprehensive risk zoning map showed that most cities of Jiangsu Province are at the moderate risk level, and the northwestern cities have lower risk level than the southern cities. The results are consistent with the actual situation of Jiangsu Province, and the study can provide some decision-making references for the urban rainstorm management.

Fuzzy risk analysis of dam overtopping from snowmelt floods in the nonstationarity case of the Manas River catchment, China

With the significant climate change that has occurred in the Manas River catchment, the temporal and spatial patterns of the natural changes in the regional water cycle have changed dramatically in the past 30 years, and the frequency of extreme hydrological events has increased, which has changed the overall stability of the hydrological system of the catchment. According to the annual maximum peak flow data for the period 1956–2014 in the Manas River catchment, we used variable fuzzy set theory and the Mann–Kendall test to conduct trend and change point tests, respectively, and decomposition synthesis theory was used to handle consistency correction. Combined with the flood routing results for the Kensiwate reservoir using Monte Carlo simulation, a reservoir overtopping risk model based on right-angle trapezoidal fuzzy numbers was established, and the fuzzy risk index intervals and the corresponding fuzzy risk rate intervals for the Kensiwate reservoir were considered for past and present conditions. The results show that the local tendency and jumping of the maximum flood peak series showed significant changes; the annual runoff had an obvious growth trend in the period 1985–2006 and a gradually varying qualitative change from 1975 to 2000. In particular, the characteristic parameter reached an extreme qualitative change level of − 0.0016 in 1993. Then, we used decomposition synthesis theory to process the sequence with jumping points and obtained the past and present hydrological time series. Under the present conditions, the average flood peak sequence is 58.10% higher than in the past, and the flood design value decreases with increasing design frequency; however, when the present sequence increases, the change rates of both flood design values increase. The reservoir overtopping risk increased under the current conditions of snowmelt floods, which was affected by a significant increase in catchment temperature. Moreover, the use of right-angle trapezoidal fuzzy numbers to describe the reservoir overtopping risk was more in line with the objective reality than a traditional triangular fuzzy number. The results of this study can be used for the efficient utilization of water resources in the Manas River catchment and provide a new reference for the scientific management of reservoirs.

Coupled Model of Variable Fuzzy Sets and the Analytic Hierarchy Process and its Application to the Social and Environmental Impact Evaluation of Dam Breaks

Dam construction is important for economic development. However, the safety risks posed by dangerous dams are unacceptable. The need for the consequence evaluation of dam breaks has been increasing to reduce all types of losses caused by dam breaks in downstream areas. However, research on this topic is relatively scarce, particularly in the field of social and environmental impact assessments. This study combined the analytic hierarchy process, variable fuzzy set, and an index system to overcome the limitations of traditional evaluation methods and the problem in which the obtained evaluation level cannot be located accurately. An integrated variable fuzzy evaluation model was proposed to evaluate the social and environmental impact of dam breaks. To explore and compare the presented method with other traditional methods, a case study of the Changlong Reservoir was conducted. The comparison results showed that the proposed method features accurate algorithms and a scientific evaluation process. It can convey the severity of social and environmental impact to a certain degree by using the eigenvector of level H, which can improve the accuracy of assessment results. Meanwhile, various factors in the object to be evaluated were comprehensively considered. Therefore, the proposed method can be applied to the social and environmental impact evaluation of dam breaks.

Evaluation of environmental impact of construction waste disposal based on fuzzy set analysis

Abstract Construction waste brings great trouble to urban environmental management. The traditional construction waste disposal method has high operability and low cost. In this paper, the core concept of set pair analysis ”connection degree” and the core concept of variable fuzzy set theory ”difference degree” are essentially the same, and the improved and refined set pair analysis connection degree function is combined with variable fuzzy set theory. The concept of relation degree is used to simplify the formula of difference degree. The obtained characteristic function is substituted for the relative difference degree function in the variable fuzzy set, to establish the fuzzy set pair analysis evaluation model and realize the complementary advantages of the theory of set pair analysis and variable fuzzy set. The experimental results show that the evaluation results of the model presented in this paper are objective and reasonable, and more comprehensively reflect the impact of different construction waste disposal methods on the environment. At the same time, the construction process of fuzzy difference degree is simplified, the evaluation efficiency is improved, and a scientific method is provided for the evaluation of the environmental impact of different treatment methods of construction waste.

Evaluation of Dam Break Social Impact Assessments Based on an Improved Variable Fuzzy Set Model

In recent years attention has shifted from “dam safety” to “dam risk” due to the high loss characteristics of dam breaks. Despite this, there has been little research on social impact assessments. Variable fuzzy sets (VFSs) are a theoretical system for dealing with uncertainty that are used in many industries. However, the relative membership degree (RMD) calculations required for VFSs are complicated and data can be overlooked. Furthermore, the RMD is highly subjective when dealing with qualitative problems, which can seriously affect the accuracy of the results. This study introduces grey system theory (GST) which analyzes the RMD characteristics to improve traditional VFSs. A new method for calculating the social impact of a dam break is proposed based on the correlation between the core parameters of the two theories. The Liujiatai Reservoir is used as a test case and the new and traditional evaluation methods are compared. The results show that the proposed method has advantages when dealing with uncertainty that are consistent with the characteristics of the problems associated with dam break social impact assessments. Moreover, the evaluation results obtained using the proposed method are consistent with, or more accurate than, those obtained using the traditional method.

Research on a Safety Assessment Method for Leakage in a Heavy Oil Gathering Pipeline

At present, the number of oil and gas gathering and transportation pipelines is numerous, and leakage accidents occur frequently. Each year, due to pipeline failure, there are immeasurable consequences for people and the environment around the affected pipelines. In order to reduce the risk of leakage accidents in heavy oil gathering pipelines and prevent the occurrence of major spills, it is of great significance to carry out safety assessments of them. However, failure data of these pipelines is seriously deficient and statistical methods used to evaluate pipeline safety are incompatible. Therefore, this paper proposes a risk assessment system for heavy oil gathering pipelines in the absence of failure data. Firstly, a Bayesian network (BN) for the leak safety evaluation of heavy oil gathering pipelines is established via mapping from a bow-tie (BT) model. Then, information diffusion theory is combined with fuzzy set theory to obtain the failure probability of each factor affecting the pipeline failure, and then the failure probability of the pipeline is obtained by the full probability formula. In addition, in order to assess the extent of consequences due to accidents, variable fuzzy set theory is used to comprehensively consider the consequences of the leakage of heavy oil gathering pipelines. Finally, the above two parts are combined to form a safety assessment system to realize risk management and control for pipelines, which is necessary to ensure the safety of heavy oil gathering pipelines.