Variable Fuzzy Set Research Articles

Risk Evaluation Based on Variable Fuzzy Sets and Information Diffusion Method

Risk evaluation is an effective way to reduce the impacts of natural hazards and it plays an increasingly important role in emergency management. Traditional methods of assessing risks mainly utilize Geographic Information System (GIS) to get risk map, and information diffusion method (IDM) to deal with incomplete data sets. However, there are few papers discuss the uncertainty of integrated hazards and consider dynamic risk under time dimension. The model proposed in this study combines the variable fuzzy set theory with information diffusion method (VFS-IDM) to solve the uncertainness of multiple hazards dynamic risk assessment when data sets are incomplete. This study employs fuzzy set theory (VFS) to calculate the relative membership degree and applies information entropy method (IEM) to obtain the weights of criteria indicators for multiple hazards evaluation. Then applies information diffusion method (IDM) to estimate condition probability distribution and vulnerability curve with the VFS-IEM model results, time data and multiple hazards losses. Then the expected value of multiple hazards dynamic risk can be calculated by using the normal information diffusion estimator so as to improve the accuracy of risk evaluation results.

Environmental impact evaluation model of dam breach — considering the uncertainty feature of environment

The environmental impact of dam breach has the features of complexity and uncertainty. There is a lack of systematic and comprehensive research on the environmental impact of dam breach in China. Considering such fuzziness of environment evaluation and the lack of precise data, this work chooses the method of multi-index comprehensive evaluation. Targeting to solve the uncertainty problem of weight calculation and evaluation model, this work introduces the statistic cloud theory to calculate the weight and variable fuzzy set theory to evaluate the environmental impact. We select seven environmental impact factors, including channel morphology, vegetation coverage, water and soil environment, biodiversity, human ecology, and industrial pollution, are selected to construct the evaluation index system and construct the value standard of them. The models are applied to the dam of Shaheji Reservoir in China. The results show that the environmental impact degree of the reservoir member an extremely serious grade mostly, reaching 0.589. Compared with the evaluation results already done, the result of the proposed models shows that the models are reasonable and scientific, which provides a new method for environmental impact assessment of dam breach considering the uncertainty feature of the environment.

A New Risk Assessment System Based on Set Pair Analysis – Variable Fuzzy Sets for Underground Reservoirs

The effects of underground reservoir operation have important scientific significance and application value for the development, utilisation, and management of groundwater resources. Based on the investigation of hydrogeological conditions and operation management of the Dagu River underground reservoir, a new assessment system for the operation effects of the underground reservoir was established. In this study, water quantity, water quality, pollution source, vulnerability, and economic benefits of the underground reservoir were considered assessment indexes.. And we used a coupled set pair analysis and variable fuzzy set (SPA-VFS) to evaluate the Dagu Rive underground reservoir. The assessment results show that the assessment indexes of groundwater exploitation rate, groundwater exploitation modulus, wastewater treatment rate, and economic benefit ratio are good, but the water quality of the reservoir area is usually poor, the fertilizer application rate is high, and the aquifer vulnerability is weak.

Evolution characteristics and variability analyzation of rainfall and runoff based on time scale

With the rapid development of economy, the hardening area of city is increasing, which leads to the change of the runoff production law in the city. In order to understand the change of urban rainfall and runoff in the changing environment, the control basin of the Dahongmen hydrological station of Liangshui river in Beijing was selected as the research object. Mann - Kendall nonparametric rank correlation test, Non-parametric Pettitt test and qualitative and quantitative models of the Variable fuzzy set were used to study the evolution characteristics and variability of rainfall and runoff based on the measured data from 1980 to 2015. The results show that the flood peak and flood amount in the 1990s were smaller than those in 1980s, and the flood peak and flood amount were significantly greater than those in the 1980s and 1990s after 2000. The actual maximum flood peak and flood amount had significantly rising trend. For variability analysis, the mutation point of annual rainfall and runoff occurred in 1996 and 1993 respectively. They did not change qualitatively on the time scale, but only showed the quantitative variation. This study results can provide a basis for rational decision of flood prevention departments.

A Novel Method in Surface Water Quality Assessment Based on Improved Variable Fuzzy Set Pair Analysis.

In the case of surface water pollution, it is important and necessary to accurately assess the level of contaminated water and ensure the safety of drinking water for people in disaster areas during floods. However, for the assessment of the strict requirements of drinking water, traditional assessment methods still have some limitations, such as low precision and rationality. In order to overcome these limitations, in the light of the theory of set pair analysis and variable fuzzy set, we propose an improved variable fuzzy set pair analysis method (IVFSPA), which combines the analysis framework of variable fuzzy set and set pair analysis, and has made some improvements to the fusion architecture. Firstly, we present a novel game theory comprehensive weighting method, in which the objective entropy method and the subjective analytic hierarchy process(AHP) method employed to obtain the reasonable weight. Then, based on the Nemerow index method, we improve the arithmetic form of “” (Equation P) to replace the fuzzy comprehensive evaluation method. Furthermore, we design a double judgment mode of combining the principle of maximum membership degree with the positive and negative relationship between the standard value and the measured value, which can accurately judge the evaluation level of surface water quality. Finally, to validate and verify the effectiveness of the proposed method, experiments was conducted at the representative river collection sections of Nanking, China, employing water quality data of 14 sampling sections in their rivers in Nanking during the 2017 flood. In terms of performance metcrics of precision and rationality, based on the values of “TP”, “NH3-N”, “Pb”, “AS” and “KMnO4” of “Ch-lh section/Chuhe gate” are 0.415, 3.77, 0.07, 0.23 and 7.12, respectively, the level of Ch-lh section/Chuhe gate is that the IVFSPA is Class V and the rest are class IV. Results of experiments show that our IVFSPA method can achieve a good performance, compared with other traditional methods.

Comprehensive Prediction and Discriminant Model for Rockburst Intensity Based on Improved Variable Fuzzy Sets Approach

Rockburst intensity prediction is one of the basic works of underground engineering disaster prevention and mitigation. Considering the dynamic variability and fuzziness in rockburst intensity prediction, variable fuzzy sets (VFS) are selected for evaluation and prediction. Here, there are two problems in the application of traditional VFS: (i) the relative membership degree (RMD) calculation process is complex and time-consuming, and the RMD matrix of all indexes can be only obtained by using the RMD function repeatedly; (ii) unreasonable weights of indicators have great impact on the synthetic relative membership degree (SRMD), so it is difficult to guarantee the correctness of the final prediction result. In view of the above problem, this paper established three simplified feature relationship expressions of RMD based on VFS principle and used the SRMD function to establish a BP neural network model to optimize SRMD. The improved VFS method is more efficient and the prediction results are more stable and reliable than the traditional VFS method. The main advantages are as follows: (1) the improved VFS method has higher computational efficiency; (2) the improved VFS method can verify the correctness of RMD at all times; (3) the improved VFS method has higher prediction accuracy; and (4) the improved VFS method has higher fault tolerance and practicability.

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.

Flood-Risk Zoning Based on Analytic Hierarchy Process and Fuzzy Variable Set Theory

AbstractThis study investigated torrential rain and waterlogging disasters in Henan Province combining the analytic hierarchy process method with the theory of fuzzy variable sets, and applying Arc...

Assessing mine water quality using a hierarchy fuzzy variable sets method: a case study in the Guojiawan mining area, Shaanxi Province, China

It is essential to assess mine water quality before this resource can be comprehensively utilized. The objective of this paper was to develop an integrated approach that can be applied for mine water quality assessment. An improved analytic hierarchy process (IAHP) method was used to calculate the weights of evaluation parameters, while fuzzy variable sets were used to determine the classification of mine water quality. Guojiawan mining area in Shaanxi Province, China, was chosen as the study area for this research and concentrations of total dissolved solids, chemical oxygen demand, chloride, sulfate, fluoride, and arsenic, as well as pH were utilized as water quality assessment factors. A total of 16 water samples, 13 samples from Guojiawan coal mine and three samples from Beiniuchuan River near the mine, were collected. The results show that four of these samples belonged to class III (roof water and river water) and encompass 25% of the total, and it can be used for domestic drinking, irrigation and industrial purposes, directly. While three belonged to class V and were derived from the auxiliary and main haulage roadways as well as the 51140 face cutting. They can be used for some industrial purpose after corresponding treatment. This latter group of samples accounted for 18.75% of the overall total, while the remaining nine were evaluated as class IV, encompassing 56.25% of the total, and they can be used for irrigation directly and domestic drinking after proper treatment.

Research on Water-Filled Source Identification Technology of Coal Seam Floor Based on Multiple Index Factors

According to the No. 13 Mine of Pingdingshan Coal Co. Ltd., the fault dimension of the study area is calculated based on fractal theory. The four impact factors such as water inflow, water pressure, water inrush coefficient, and fault fractal dimension of 21 water boreholes are used as evaluation indices, and a mathematical model for identifying the water-filled source of the coal seam floor is established by coupling an entropy weight method and fuzzy variable set theory. The model is used to identify the water-filled source of 7 boreholes, which provide a reliable reference for the identification of the water-filled source. According to the calculation result of the entropy weight method, the water volume per unit of the borehole and the groundwater pressure have a significant impact on the water source identification, which accounts for 89.93% of the weight value. In the fuzzy variable set model, when the distance parameter p is 1 and the optimization criterion parameter α is 2, the accuracy of the water sample identification of the water source category to be identified is 85.71%, which is at a high recognition level. The more typical the impact factors selected and the more samples, the accuracy of water-filled source identification is much higher.

Estimating winter wheat area based on an SVM and the variable fuzzy set method

ABSTRACTThis paper proposed a method of extracting the winter wheat area by combining support vector machine (SVM) with variable fuzzy sets. This method mainly aims to deal with mixed pixels in remote sensing images. The SVM classifier can accurately identify pure winter wheat pixels with training samples. However, winter wheat area information in mixed pixels cannot be directly obtained because they contain multiple types of features. In order to estimate the winter wheat area information of mixed pixels in Landsat8 data, this paper introduced the normalized difference vegetation index (NDVI) and the variable fuzzy set method. Finally, this paper reasonably estimated the area of winter wheat from the mixed pixels in Landsat8 images. The accuracy assessment showed that the proposed method could extract winter wheat area information more accurately.

A novel algorithm based on information diffusion and fuzzy MADM methods for analysis of damages caused by diabetes crisis

Diabetes mellitus is one of the most common chronic diseases in the world. A remarkable point about chronic diseases is that patients may be involved in related complications throughout their lifetime. Management and control of chronic diseases are one of the most costly and important issues in the healthcare field due to their long term treatment period. In this paper, the number of patients involved in complications of type II diabetes has been studied in 19 years and the goal is to calculate the severity of damage caused by diabetes by a new hybrid algorithm which is consisted of multi criteria decision making, variable fuzzy set theory and information diffusion method for the first time. However, the traditional probability statistical methods ignore the fuzziness of risk assessment with incomplete data sets and require a large sample size of data, the new proposed algorithm deals effectively with these challenges and produces more accurate results with fewer errors. For example in terms of working with small data samples, it will be shown that the mean error of results produced by hybrid algorithm is 0.0198 while it is 0.0264 for multiple regression and 0.0299 for cox proportional hazard method which means 33.3% and 51% error increase in proportion to hybrid algorithm respectively.

A new method of the relative membership degree calculation in variable fuzzy sets for water quality assessment

The wide application of variable fuzzy sets theory (VFST) in water quality evaluation indicates that the calculation process of relative membership degree (RMD) is complicated and laborious. The traditional method of calculating RMD repeatedly reuses the relative membership degree function (RMDF), and lacks an effective means to estimate the reliability of the calculation. These problems increase the difficulty of water quality evaluation. Based on the principle of variable fuzzy sets, this research finds some data characteristics of RMD and further demonstrates its inevitability. A new method was developed using a combination of these data characteristics and the traditional method of RMD calculation. By empirical analysis of water quality evaluation, the new method exhibited stable reliability and efficient performance compared with the traditional method. The primary advantages include the following: (i) simplification of the calculation of RMD and reduction in the computation burden for RMDF, (ii) verification of the calculation result of RMD and development of a scientific basis for testing evaluation results, and (iii) improvement of the calculation accuracy of RMD.

A Comprehensive Evaluation Model for Irrigation Districts Modernization Based on Variable Fuzzy Sets

The evaluation of irrigation district modernization is the basis of the construction of modern irrigation district and has an important reference for the irrigation district modernization. The indicators and evaluation index system were discussed and thresholds of irrigation districts indicators were analyzed. A mathematical model for the evaluation of modern irrigation districts was established based on variable fuzzy set theory. Taking the Panzhuang plain irrigation district in Shandong Province and the Tongziba plateau irrigation district in Gansu Province as an example, the situation of the irrigation district after modernization was evaluated. After the modernization of Panzhuang irrigation district and Tongziba irrigation district, the evaluation result is H=1.382, 1.448, respectively, which is all in full realization of modernization. Compared with the current status of irrigation district, it shows that the modernization measures of irrigation districts are reasonable and effective for irrigation district.

Agricultural Drought Risk Evaluation Based on an Optimized Comprehensive Index System

In this study, a new optimized comprehensive drought index system (OCDIS) was developed based on pressure-state-response (PSR) and random forest (RF). Then the pressure, state, response, and integrated agricultural drought risk were evaluated according to the synthetic-weight variable fuzzy set (SW-VFS) model. Finally, the countermeasures in terms of pressure, state, and response were discussed. The proposed index has been implemented in Qujing, Yunnan Province, China. The results showed that of the 10 indices included in the OCDIS, the four most important indices for agricultural drought risk management are reservoir storage capacity, precipitation anomaly percentage, soil moisture, and per capita annual income. The pressure risk and response risk of Malong are relatively higher than other counties. The integrated results indicated that most counties of Quijng have moderate drought risk. The assessment results are consistent with the actual situation of Qujing. The proposed model provides a scientific and objective way to develop the risk index system of agricultural drought. This study can potentially assist government agencies with information on the most important drought impacts and provide the basis for science-informed decision-making.

The use of an integrated variable fuzzy sets in water resources management

Abstract. Based on the evaluation of the present situation of water resources and the development of water conservancy projects and social economy, optimal allocation of regional water resources presents an increasing need in the water resources management. Meanwhile it is also the most effective way to promote the harmonic relationship between human and water. In view of the own limitations of the traditional evaluations of which always choose a single index model using in optimal allocation of regional water resources, on the basis of the theory of variable fuzzy sets (VFS) and system dynamics (SD), an integrated variable fuzzy sets model (IVFS) is proposed to address dynamically complex problems in regional water resources management in this paper. The model is applied to evaluate the level of the optimal allocation of regional water resources of Zoucheng in China. Results show that the level of allocation schemes of water resources ranging from 2.5 to 3.5, generally showing a trend of lower level. To achieve optimal regional management of water resources, this model conveys a certain degree of accessing water resources management, which prominently improve the authentic assessment of water resources management by using the eigenvector of level H.

Introducing Biological Indicators into CCME WQI Using Variable Fuzzy Set Method

The biological indicators are rarely used in CCME WQI, for the objective thresholds of most biological indicators are ambiguous. To solve this problem, this study establishes an improved CCME WQI model based on variable fuzzy set theory. The water quality of Wuli Lake is assessed as an illustration; and the result shows that its water quality condition is “fair”, and more measures should be adopted to control the internal phosphorus releasing and the reproduction of cyanobacteria in summer and autumn. Moreover, compared with the conventional CCME CQI, the improved CCME WQI is more comprehensive, for it not only takes the aquatic physic-chemical condition into consideration, but also introduces the biological indicators into evaluation.

Probabilistic Variable Precision Fuzzy Rough Set Technique for Discovering Optimal Learning Patterns in E-learning

In e-learning environment, optimal learning patterns are discovered for realising and understanding the effective learning styles. The value of uncertain and imprecise knowledge collected has to be categorised into classes known as membership grades. Rough set theory is potential in categorising data into equivalent classes and fuzzy logic may be applied through soft thresholds for refining equivalence relation that quantifies correlation between each class of elucidated data. In this paper, probabilistic variable precision fuzzy rough set technique (PVPFRST) is proposed for deriving robust approximations and generalisations that handles the types of uncertainty namely stochastic, imprecision and noise in membership functions. The result infers that the degree of accuracy of PVPFRST is 21% superior to benchmark techniques. Result proves that PVPFRST improves effectiveness and efficiency in identifying e-learners styles and increases the performance by 27%, 22% and 25% in terms of discrimination rate, precision and recall value than the benchmark approaches.

基于可变模糊集合理论的农业生态环境评估系统研究

基于可变模糊集合理论的农业生态环境评估系统研究

Risk Assessment of Drought, Based on IDM-VFS in the Nanpan River Basin, Yunnan Province, China

A new model for risk assessment of agricultural drought based on information diffusion method and variable fuzzy sets (IDM-VFS) was proposed. In addition, an integrated index system of agricultural drought risk was established. In the proposed model, IDM was employed to calculate the agricultural drought risk level classification standards, and then the VFS was adopted to assess the dangerousness, sensitivity, vulnerability, and comprehensive risk of agricultural droughts. In the present study, Nanpan River Basin was employed to assess the agricultural drought risk with the proposed model. The results showed that KaiYuan, ShiZong, QiuBei, and ZhanYi have higher dangerousness, due to water shortage. GuangNan have higher sensitivity and vulnerability because of lower drought resistance level and higher crop planting proportion. The comprehensive agricultural drought risk shows apparent regional characteristics: the central, western and northwestern counties have lower risk than the eastern counties. Moreover, most areas of the Nanpan River Basin are of moderate agricultural drought risk grade. The results are consistent with the actual situation of Nanpan River Basin and verify the model’s effectiveness. The study can provide a scientific reference in drought risk management for local governmental agencies.