Principle Of Maximum Membership Degree Research Articles

Research on a Classification Method of Goaf Stability Based on CMS Measurement and the Cloud Matter–Element Model

The evaluation and classification of goaf stability are fuzzy and random. To address this problem, a new classification method is proposed. A cavity monitoring system is used to detect the goaf, 3DMine and FLAC3D software are used to conduct the 3D visual modeling of the scanning results, and numerical simulation analysis is performed on the goaf. According to the analysis results, the stability classification standard of the goaf is constructed, and the characteristics of each classification are described. The evaluation indicator system of goaf stability is constructed in accordance with similar engineering experience, and the evaluation indicator is weighted by using the analytic hierarchy process. The cloud–element coupling evaluation model is built, the field measured values of indicators are collected, the cloud correlation degree of goafs belonging to each stability level is calculated, the stability level is evaluated according to the principle of maximum membership degree, and the results are compared with the numerical simulation to analyze the reasons for the differences in the stability evaluation results obtained by the two methods and to improve the accuracy of the evaluation of goaf stability. The pillar stress and surrounding rock deformation are monitored in Room 1# of the inclined mining area of Shirengou Iron Mine. The monitoring results are consistent with the evaluation results, which proves the accuracy of the proposed goaf stability classification method.

A novel grade assessment method for cybersecurity situation of online retailing with decision makers’ bounded rationality

The online retailing cybersecurity situations grade assessment (GS) is a key issue in cybersecurity management, which can be regarded as a type of multi-attributes GS problems. However, traditional GS methods rarely discuss the boundary fuzziness and hesitation in the grade classification of attributes, as well as the monotony relation and interrelation between entropy fuzziness and intuitionism. A novel GS method with respect to decision makers’ bounded rationality is proposed. To get the method, the membership functions (MFs) and non-membership functions (NMFs) of attributes’ eigenvalue grade considering decision maker s’ bounded rationality and hesitation are proposed. An axiomatic definition of IF entropy on the basis of isentropic arcs is proposed, providing the formula of the monotony relation and interrelation between fuzziness and intuitionism. We, considering the reliability and the IF grade assessment method, propose the similarity of IF grade eigenvalue, which identifies grades reasonably and distinguishes the ranking of the same grade, and overcomes the defect that the maximum membership degree principle ignores the position differences of each grade assessment level.

Research on distribution network operation status evaluation technology based on new sensing measurement method

The access to distributed power supply and large-scale load increases the complexity of the distribution network, resulting in the decline of traditional monitoring accuracy and the difficulty of distribution network operation status assessment. This paper proposes a distribution network operation status assessment technology based on a new sensing measurement method to provide a foundation for the stable operation of the distribution network. The operating state evaluation system is constructed by the operating standard of the distribution network, including 6 types of upper indicators and 14 bottom indicators. The analytic hierarchy process (AHP) was used to calculate the weight factor of the evaluation index. Fuzzy mathematics is used to evaluate the operating state of the distribution network, a fuzzy matrix is established, and the evaluation results are calculated according to the principle of maximum membership degree. Finally, the validity and rationality of the proposed method are verified by the sensing measurement data.

A fuzzy multiobjective team decision model for CODP and supplier selection in customized logistics service supply chain

To address information vagueness and uncertainty of the order demand, the logistics service provider (LSP) service capacity and the target preference caused by emergency events, a multiobjective team optimization model is developed for the customer order decoupling point (CODP) decision, supplier selection and order quantity allocation problems in customized logistics service supply chain. Three important techniques are described: (1) Fuzzy objective coefficients due to the uncertainty of the order and objective weights. (2) Fuzzy constraint parameters due to LSP service capacity and order demand variations. (3) A fuzzy single objective weighting technique with acceptance coefficient of constraint and fuzzy parameters that reflects decision-maker preferences. The acceptance coefficients of the constraints are integrated into the single objective model, which reflects the satisfaction level of the logistics service integrator (LSI) for feasible solutions. Then, we perform fuzzy decision and feasible solution design based on the center of gravity method defuzzification and maximum membership degree principle. To optimize decisions for decision-makers, the effects of some important fuzzy objective coefficients and fuzzy constraint parameters on the CODP decision and the acceptance coefficient of constraint was explored through sensitivity analysis. Numerical experiments show that the scale effect coefficient and objective function threshold have greater effects on the CODP decision.

Evaluation Model of Urban Resilience in the Face of Public Health Emergencies: A Case Study of Xi’an

In recent years, there have been frequent outbreaks of public health emergencies worldwide, especially resulting from the COVID-19 pandemic, which has seriously affected social and economic development and people’s production and life. In order to avoid or minimize the harm caused by these emergencies to society and the public, this article constructs a resilience indicator system for urban emergency response capabilities based on resistance, adaptation, and recovery. We establish a dynamic model of urban emergency response resilience, select the infectious disease dynamics method as the index weight calculation method, analyze the correlations among various indicators and parameters of the urban emergency response resilience system, and conduct sensitivity analysis on the model parameters to determine the importance sequence of each model parameter. Combined with the fuzzy hierarchy analysis method, we evaluate the model and use the 2021 year-end epidemic in Xi’an as an example to evaluate the urban emergency response resilience level using the evaluation model. According to the maximum membership degree principle, the results show that the emergency resilience levels of Xi’an were “moderately strong”, “moderately strong”, and “strong” in the first, second, and third stages of the epidemic, respectively. The results demonstrate that the method proposed in this article can objectively reflect the current level of urban emergency resilience and provide some references and guidance for improving the resilience of urban emergency response to public health emergencies.

Risk assessment of deep excavation construction based on combined weighting and nonlinear FAHP

Deep excavation construction safety has become a challenging and crucial aspect of modern infrastructure engineering, and its risk assessment is frequently carried out using the Fuzzy Analytic Hierarchy Process (FAHP). However, when using FAHP to evaluate the risks of deep excavation construction, the results of the weightings obtained through subjective weighting are heavily influenced by the subjective factors of the evaluators. In addition, using linear operators to calculate the risk level can easily cause a weakening effect on the influence of prominent risk factors, resulting in poor rationality of the evaluation results. To address these problems, this paper constructs a deep excavation construction risk evaluation model based on combined weighting and nonlinear FAHP. The WBS-RBS method is used to guide the construction of the risk evaluation index system for deep excavation construction. The combined weighting values of subjective and objective weightings are calculated through the game theory combined weighting method. The fuzzy relation matrix is constructed using the membership degree vector obtained from the expert evaluation method. Nonlinear operators are introduced for comprehensive calculation. According to the maximum membership degree principle, the final risk level of the excavation construction is obtained. The newly constructed model is applied to the risk analysis of the deep excavation construction of the Rongmin Science and Innovation Park project in Xi’an. The evaluation result for the excavation construction risk is N= [0.3125, 0.3229, 0.1939, 0.0854, 0.0854], and according to the maximum membership degree principle, the risk level of the excavation is classified as Level 2, which is a relatively low risk. Based on the deep excavation construction of the Rongmin Science and Innovation Park project, this paper discusses the differences between the new model and the traditional FAHP evaluation method, further verifies the reliability of the new model, optimizes the construction plan based on the evaluation results, avoids risks, and determines its guiding significance.

The Application of Fuzzy Mathematics in the Optimization of the Recipe of Filling Paste for Coal Mine Backfill

Backfill is a very important technology that can be used to reduce the environmental footprints resulting from coal mining. The selection of proper filling materials is of great significance to the operation cost and the stability of the goaf. This paper investigated the feasibility of using the coal gangue as the main component of the filling paste so as to reuse the byproducts in coal mining to the maximum extent. The filling pastes were composed of coal gangue as the aggregates, cement or gypsum as cementitious materials, and some additives. In order to determine the optimal recipe, the performances of filling pastes were first comprehensively evaluated according to their fluidity, mechanical properties, shrinkage, and permeability. The results showed that cement content was the most influential factor, while the fly ash addition was the weakest factor for the performance of filling pastes. Moreover, the appropriate use of a water reducer and expansion agent improved the working performance of the paste. Based on the performances of filling pastes, the fuzzy mathematics evaluation method was then used to establish the weight vector and index vector. The principle of maximum membership degree and the principle of maximum closeness were used to identify the identified objects and find the best recipe for the filling paste. The results showed that this evaluation method could fully reflect the influence of various factors and provide accurate evaluation results.

Risk uncertainty analysis in shield tunnel projects

Subway shield tunnels usually pass through the complex geological environment of a city. There are many uncertain factors in shield tunnel construction risk, undoubtedly increasing the difficulty of construction safety control. Risk evaluation prior to project construction is necessary for the implementation of tunnel projects and reduces risk levels during construction. However, tunnel risks are uncertain and are characterized by random and fuzzy uncertainty. To account for these two uncertainties in the quantitative transformation of risk qualitative concepts and to improve the evaluation accuracy, in this study a new risk evaluation method based on a two-dimensional cloud model (TDCM) is proposed for shield tunnel projects. First, the risk evaluation criteria are quantified with the harmfulness and the probability of risk as the evaluation dimensions of the two-dimensional cloud, and the conversion relationship between the risk level and the quantitative domain is improved. A risk evaluation index system based on construction accidents and risk types for shield tunnel projects is established. Then, the Delphi method is used to evaluate the probability and harmfulness of the risk, the index weight and numerical characteristics of the two-dimensional cloud model are determined, and a shaped two-dimensional comprehensive cloud of thousands of cloud droplets is generated by a positive cloud generator. Finally, the domain is defined as the overlap between the comprehensive evaluation cloud and the standard cloud at different risk levels, and the contribution of comprehensive evaluation cloud drops to the comprehensive evaluation cloud in each domain is analysed. The risk level of the project is predicted based on the principle of maximum membership degree. The risk evaluation method proposed in this study is applied to two subway shield sections, and the risk level of these projects is accurately predicted. The TDCM evaluation method is compared with the one-dimensional cloud model (ODCM) evaluation method and the fuzzy comprehensive evaluation method (FCEM), and the advantages and applicability of the TDCM evaluation method are discussed.

Tunnel collapse risk assessment based on improved quantitative theory III and EW-AHP coupling weight.

It is a multi-criteria decision issue to conduct a risk assessment of the tunnel. In this paper, a tunnel collapse risk assessment model based on the improved theory of quantification III and the fuzzy comprehensive evaluation method is proposed. According to the geological conditions and the construction disturbance classification method, the evaluation factors are selected, and the tunnel collapse risk level is divided into 5 levels according to the principle of maximum membership degree. The three groups of scores with the largest correlation ratio are calculated by the theory of quantification III to form the X, Y, and Z axes of the spatial coordinate system, The spatial distance of each evaluation factor is optimized by the Kendall correlation coefficient combined with the empirical formula, so that it can be used to judge the probability of the occurrence of the evaluation factor; taking the coupling of the objective entropy weight method (EW) and the subjective analytic hierarchy process (AHP) as the weight. Finally, the fuzzy comprehensive evaluation method is used to determine the possibility classification of tunnel collapse. Taking the Ka-Shuang water diversion tunnel as a case study, the comparison between the evaluation results of 10 tunnel samples and the status quo of the actual engineering area verifies the reliability of the method.

Application of Modified Cloud Model-Level Eigenvalue Method in water quality evaluation

Groundwater quality is affected by numerous uncertain factors, and the evaluation process is liable to randomness and fuzziness. To evaluate the quality of groundwater effectively, this study proposed a multi-index evaluation system termed the Modified Cloud Model-Level Eigenvalue Method (MCM-LEM) model, which is based on cloud model theory. In this evaluation system, the water quality was classified into five levels and several parameters were selected, while the CRITIC objective weight method is used to calculate the weight of each evaluation parameter, before an One-dimensional Normal Cloud Model and a Multi-dimensional Normal Cloud Model are established to obtain the membership degree of water samples pertaining to each water quality level. Finally, the LEM was used to assess the water quality level. In this study, taking the groundwater in the urban area of Jilin City as an example, seven evaluation parameters were selected for water quality evaluation, and the water quality evaluation results using the MCM-LEM model were compared with those obtained via the Single Factor Evaluation Method, the Nemerow Index Method and the Fuzzy Comprehensive Evaluation Method. The evaluation results obtained via the MCM-LEM model were largely consistent with those obtained via the other methods. Compared with the other methods, the MCM-LEM model can comprehensively consider the fuzziness and randomness, as well as the correlation between them; can avoid complex function calculations; and can provide more scientific and objective evaluation results. Furthermore, compared with the One-dimensional Normal Cloud Model, the Multi-dimensional Normal Cloud Model comprehensively considers multiple evaluation parameters, which simplifies the modeling process and reduces the calculation times for the membership degree. Meanwhile, using the LEM to determine the water quality level not only overcomes the inapplicability of the Maximum Membership Degree Principle, but also allows for assessing the relative advantages and disadvantages of different water samples of the same level. The proposed method can be used to the evaluation of the groundwater quality in other areas, enabling the planning and management of groundwater resources.

Evaluation of Tourism E-Commerce User Satisfaction

According to the UNWTO, within 4 to 5 years, the proportion of tourism e-commerce in e-commerce will reach 20%-25%. The purpose of this paper is to improve the inadequacy of tourism e-commerce in customer experience, to conduct customer e-commerce satisfaction surveys, and to draw customers' dissatisfaction with tourism e-commerce. The experimental results show that the overall customer satisfaction is 2.6128. According to the division of the scale vector, the overall satisfaction of the travel e-commerce customers is generally level. The first-level fuzzy comprehensive evaluation is 0.0967, 0.1696, 0.3366, 0.2469, 0.502. According to the principle of maximum membership degree, the evaluation grades of R3 and R5 in the first-level fuzzy comprehensive evaluation are “unsatisfactory,” that is, the tourism-supporting services and contract-performance services become the main factors affecting customer satisfaction. In order to improve customer satisfaction, the tourism e-commerce platform should strengthen the management of tourism-supporting services and contract-fulfillment services.

Groundwater runoff pattern and keyhole grouting method in deep mines

Deep aquifers are a common geological disaster source in coal mines and they can lead to water and mud inrush disasters. Grouting is the most effective method to reinforce aquifers and block water. However, grouting only at the water inrush area cannot obtain a stable effect. A combination of groundwater runoff analysis and grouting keyholes optimization was adopted to solve the problem of water inrush in deep mines. First, the structural pattern of the grouting area was identified and the position of the water inrush channel was deduced, yielding the mine’s groundwater runoff pattern. Then, the quality of grouting holes was evaluated by AHP analysis and the keyholes in the runoff network were determined according to the maximum membership degree principle. Finally, the keyholes were blocked by grouting. After the grouting treatment, the grouting effect was evaluated by using working face water inflow and water detection radar. The results indicate that combining groundwater runoff analysis with keyhole selection can effectively control water inrush in deep mining.

Integrated rockburst early warning model based on fuzzy comprehensive evaluation method

The development of reliable early rockburst warning models for underground mines is a challenging task considering the complex nature of rockburst phenomena. In this paper, a real-time, integrated multi-system, early rockburst warning model is developed to achieve the quantitative prediction of the rockburst probabilities at a specific time. The model input parameters are data derived from microseismic (MS) and acoustic emission (AE) monitoring systems. The early warning model is based on fuzzy comprehensive evaluation method (FCEM), confusion matrix and maximum membership degree principle. These tools integrate the advantages of both multi-system and multi-parameter into one unified model. During the early warning procedure, six early warning indices representing temporal, spatial and energy parameters are rationalized. Next, the weight of each index is determined from confusion matrix leading to a score value. Real-time early warning results can then be determined from the maximum membership degree principle. The results show that the proposed integrated MS-AE early warning model has the advantage of combining multiple systems and indices, and it has higher prediction accuracy than individual systems. The early warning model is successfully demonstrated with a case study from the Wudong Coal Mine in China. The proposed model improves the rockburst early warning efficiency and provides a solid foundation for ensuring the safety of personnel and equipment in underground mining.

A Fuzzy Comprehensive Evaluation Approach for the 3D Modeling Accuracy of UAV Oblique Photogrammetry

3D modeling is the important foundation of virtual reality and scene simulation. The technology of UAV oblique photogrammetry provides a new way for 3D modeling, and the accuracy becomes the key of its application. Since there are a lot of uncertainties in 3D modeling of UAV oblique photogrammetry, this paper proposed a fuzzy comprehensive evaluation approach to deal with this uncertain problem. Firstly, according to the composition of 3D modeling system based on UAV oblique photogrammetry, the main impact factors of 3D modeling accuracy are determined, and the indicator system of accuracy evaluation is therefore constructed. Secondly, by using the method of analytic hierarchy process, the weights and membership degrees of each indicator are calculated. Finally, the proposed approach is applied and validated in the case study. After the fuzzy mapping by the dot multiplication performance between the indicator weights and membership degrees, the comprehensive evaluation sets of different cases are obtained, and their corresponding 3D modeling accuracies can be determined based on the maximum membership degree principle. It is concluded that the fuzzy comprehensive evaluation approach proposed in this paper can quickly and correctly assess the 3D modeling accuracy of UAV oblique photogrammetry.

Assessment of Laboratory Safety in Universities Based on Combined Weighting Method and Unascertained Measure Theory

In order to avoid accidents and improve the level of laboratory safety management in universities, a laboratory safety assessment method based on entropy weight method, analytic hierarchy process and unascertained measure theory is put forward. The laboratory safety assessment index system is established by selecting eight assessment indexes such as hazardous chemicals management, instrument and equipment management and personal protective equipment management; The comprehensive weight of the assessment index is determined by combining the combination weighting method of analytic hierarchy process (AHP) and entropy weight method (EW). According to the principle of maximum membership degree, the safety grade of university laboratory is determined, and compared with the actual results. This work indicated that this innovated method can reasonably evaluate the current situation of laboratory safety, and it can provide a reference for strengthening laboratory safety management.

Research on Quality Risk Assessment of EPC Projects for Transmission and Distribution Engineering Based on Design Enterprises

Among EPC general contractors, design companies often dominate by virtue of their design advantages. However, due to the complex risks of power transmission and transformation projects throughout their life cycle, quality management is the weak point of the EPC general contractor with design as the leader, and the problems caused by quality risks are directly related to the contractor’s Economic interests and credibility. Therefore, this paper will analyze the potential quality risks in the whole process of the project, establish a risk identification list, and use the fuzzy comprehensive evaluation method to evaluate the quality risk of the EPC project of the power transmission and transformation project led by the design enterprise based on the principle of maximum membership degree.

Karst development characteristics and collapse risk assessment along Shaoxing metro line 1

Urban subway construction in karst areas can be seriously threatened by geological disasters, which impact the safety of subway construction and operation. Given the effects of geological conditions and human engineering activities, it is necessary to comprehensively analyze the influence of various factors and then evaluate the risk of karst collapse. With the section between Yanghe road station and Jianhu town station of Shaoxing metro line 1 as an example, crosshole seismic wave computed tomography (CT) was employed to prospect the geometric characteristics and spatial distribution of karst caves. Based on the survey results, ten influencing factors were selected as evaluation indexes for karst collapse susceptibility. Then, an assessment system was established, and each index was quantitatively rated through three grades. The analytical hierarchy process was used to determine the weight of these indexes, and the fuzzy transform principle and maximum membership degree principle were applied to quantitatively and comprehensively evaluate the collapse risk level in the study area. Results showed that karst cave development mainly occurred in the bedrock surface under 11 m. The caves were mostly 2–5 m high, and most of them were filled. Approximately 70% of the studied section had a moderate or high risk of karst collapse. As the subway passes through the karst area, appropriate measures should be implemented for the different risk sections to ensure the safety of construction and operation.

Accuracy Evaluation of Advanced Geological Prediction Based on Improved AHP and GPR

Ground penetrating radar (GPR) is widely used in advanced geological prediction. It is necessary to choose a scientific and effective evaluation method to give a reasonable evaluation of the accuracy of prediction. In this paper, a method based on improved analytic hierarchy process (AHP) and GPR is proposed to evaluate the accuracy of advanced geological prediction. Based on the analysis and induction of the factors that affect the accuracy of GPR prediction, an improved AHP is proposed, in which a new measure of “numerical weight” is added and the principle of maximum membership degree is integrated, and an improved AHP model is established for GPR prediction accuracy classification and evaluation. The engineering application of Xiaobeishan Tunnel of Jie-Hui Highway is taken as a case study, and it is proved that the evaluation indices are easy to obtain and the evaluation results are accurate and reliable. The improved AHP-GPR method can be further used for other tunnel engineering.

Evaluation of ecological restoration effect of rare plant Rhododendron chrysanthum population in Changbai Mountain Area

In order to study the population viability and restoration effect of Rhododendron chrysanthum population after restoration, an ecological evaluation method based on analytic hierarchy process and fuzzy comprehensive evaluation was proposed. The ecological evaluation index system was established with the help of analytic hierarchy process (AHP) and the index weight was determined. The fuzzy comprehensive evaluation method was used to evaluate the restoration effect of Rhododendron chrysanthum population from three aspects: target layer, criterion layer and index layer. The results showed that this method could effectively evaluate the ecological effect of Rhododendron chrysanthum population after restoration, in which 33% of the restoration effect of Rhododendron chrysanthum population might be “very good” and 67% might be “good”. According to the principle of maximum membership degree, the comprehensive evaluation of the restoration effect of Rhododendron chrysanthum population in the experimental area was excellent.

Fuzzy evaluation method of pipeline passing through dike based on Uncertain Analytic Hierarchy Process

In view of the characteristics of many factors influencing the safety risk of the pipeline through the embankment, which are hierarchical and uncertain, this paper combines the uncertain analytic hierarchy process (AHP) and fuzzy operation to establish a fuzzy comprehensive evaluation model. The uncertainty analytic hierarchy process (AHP) was used to determine the weight of the evaluation indicators, considering the uncertainty of the relative importance of the evaluation indicators at the same level, the credibility of experts and the degree of difference. According to the principle of maximum membership degree, the evaluation grade of the pipeline is determined. Finally, the feasibility of this method is verified by combining with specific engineering examples to reduce the potential loss and provide the safety management of the pipeline.