Variable Fuzzy Set Model Research Articles

The application of gray system-variable fuzzy sets coupling theory on the susceptibility assessment of debris flow hazards

The occurrence of debris flow hazards has significant destructive effects people’s safety and the safety of their property, so the risk assessment of debris flow hazards has great significance. The maximum amount of debris flow at one time (X1), the reserves of loose substance (X2), the watershed area (X3), the length of the ditch (X4), the relative height difference (X5), the gradient of side slope (X6), the longitudinal slope of main ditch (X7), the length ratio of replenishment section (X8), the daily maximum rainfall (X9), and Faults developed in the watershed (X10) are selected as the evaluation index at first. Then the gray system-variable fuzzy sets coupling model is introduced; secondly, the relative membership degree matrix about the fuzzy variable sets is established, and the weight coefficients considering the uncertainty of assessment indices are determined based on the entropy weight method; finally, the susceptibility level of debris flow hazards is determined using the mean ranking feature value. The conclusion is drawn that the results obtained based on the coupling technique are consistent with the current specification; its accuracy arrives at 83%, and the method is feasible for the susceptibility level assessment of debris flow hazards. Compared to the traditional variable fuzzy sets model, it avoids the uncertainty of magnitude in the standard analysis, it can ensure the objectivity and accuracy of the calculation result, and its calculation process is simple and efficient. In total, the findings of the proposed model provide an alternate way to assess the susceptibility level of debris flow hazards and improve the evaluation accuracy in the future.

A Multiple Model Approach for Flood Forecasting, Simulation, and Evaluation Coupling in Zhouqu County

Flood disasters are considered to be one of the ten natural disasters that threaten the survival of mankind. They occur frequently and have a serious impact on the national economy. For quicker response to the sudden flood, in this paper, the relevant characteristics of flood forecasting and disaster assessment are comprehensively studied to establish the corresponding models, and a multi-objective culture shuffled complex differential evolution (MOCSCDE) algorithm is proposed to optimize the model parameters. It can achieve better convergence and significantly improve the model accuracy. Then, a river hydrodynamic model is established to simulate the flooding process, and the characteristics of flood evolution, such as water depth, flow speed, duration, and submerged area, are analyzed. Third, based on the above-mentioned flood forecasting and flood evolution calculations, the relative membership function (VFS) is determined via the set pair analysis method (SPA), and the variable fuzzy set model (SPAVFS) is used for flood risk assessment. Finally, through the study of flow forecasting at Zhouqu hydrological station, it is found that the accuracy of the forecast result of the built model is best compared with LSTM and XAJ model, the mean relative error is only 7.6%, and the certainty coefficient can reach 0.96, which surpass the baselines by 20% and 7.9%.

Risk assessment method for controlled flight into terrain of airlines based on QAR data

PurposeThe purpose of this paper is to assess the risk of controlled flight into terrain (CFIT) for airlines and to develop a practical method for evaluating and predicting CFIT risk to ensure safe and efficient airline operations.Design/methodology/approachIn accordance with the monitoring project specification issued by the Flight Standards Department of the Civil Aviation Administration of China (CAAC), a preliminary draft of evaluation indicators for CFIT risk was developed based on the literature review and semi-structured interviews. Fifteen aviation experts were then selected and invited to participate in a Delphi method to revise the draft. Analytic hierarchy process (AHP) and entropy weight method were used to determine the combined weight of the indicators. The variable fuzzy set model and quick access recorder (QAR) data were applied to evaluate the CFIT risk of an airline from 2007 to 2018, and the classification results were compared with actual operational data.FindingsThe research findings reveal that the six most significant monitoring items affecting CFIT risk are incorrect configuration settings during landing, loss of altitude during climbing, ground proximity warning, G/S deviation, flap extension delay during landing and incorrect takeoff configuration. The CFIT risk of airlines has shown an increasing trend since 2015. The values in 2010, 2017 and 2018 were greater than 2 and less than 2.5, indicating that the CFIT risk is at Level 2, close to Level 3, and the risk is low but approaching medium.Practical implicationsUsing the combination weight determined by AHP and entropy weight method to rank the weight of 15 monitoring items, airlines can take necessary measures (simulator training, knowledge training) to reduce the occurrence of monitoring items with high weight to reduce CFIT risk. This risk assessment method can quantitatively evaluate the CFIT risk of airlines and provide theoretical guidance and technical support for airlines to formulate safety management measures and flight training programs, enabling the interconnection between QAR data and flight quality.Originality/valueThe proposed method in this study differs from traditional approaches by offering a quantitative assessment of CFIT risk for airlines and enabling the interconnection between QAR data and flight quality.

The Quality Assessment of Pavement Performance Using the Entropy Weight-Variable Fuzzy Sets Model

As the assessment of pavement performance has considerable repercussions for the construction quality of roads, the study of the assessment procedure used is extremely critical. Riding quality index (RQI), pavement condition index (PCI), pavement structure strength index (PSSI), skid resistance index (SRI), and antirutting index (ARI) are selected as the assessment indexes of pavement performance. Then, the entropy weight-variable fuzzy sets model is introduced. Second, a relative membership degree matrix for the variable fuzzy sets is established, and the entropy weight method is used to determine the weight coefficients considering the uncertainty in the assessment indices. Finally, the quality level of pavement performance is determined by using the mean ranking feature value. The conclusions demonstrate a very accurate rate for the quality assessment of the pavement performance based on the variable fuzzy sets model compared to that based on the current specification, and the proposed method is feasible for the quality assessment of pavement performance, thus providing a novel means of assessing the quality level of pavement performance in the future.

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.

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.

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.

Assessment on agricultural drought risk based on variable fuzzy sets model

Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was established according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respectively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combination weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the assessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.

A Variable Fuzzy Sets Model for Evaluating Urban Public Traffic Network

A Variable Fuzzy Sets Model for Evaluating Urban Public Traffic Network