Fuzzy Comprehensive Evaluation Method Research Articles

Evaluating financing risk for forest recreation value development project—A case study focused on S National Forest Park in Fujian Province

In the process of forest recreation value development, there are some characteristics, such as large amount of investment capital, long financing recovery cycle and high potential risks, which lead to limited capital source and prominent financing risks. To achieve sustainable development, forest recreational value development enterprises must solve the financing dilemma, therefore, it is very urgent to identify the financing risk factors. The research constructed financing risk evaluation index system through WSR (Wuli-Shili-Renli) methodology (from affair law, matter principle and human art dimensions), taking S National Forest Park at Fujian Province as a case study, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method were used for empirical analysis. The results showed that for the first level indicators, operational risk should be paid close attention to, followed by political risk and environmental risk. Among the secondary level indicators, policy changes, financing availability and market demand need attention, which are consistent with the result of field survey. Based on that, countermeasures were put forward such as the multiple collaborative linkage and effective internal control; reduction on operating costs and broaden financing channels; encouragement diversification of investment entities and improvement of financial and credit support; strengthening government credit supervision, optimizing financing risk evaluation, and building a smart tourism financing information platform, to reduce and control financing risks, then promote the development of forest recreation value projects.

A Fast Multi-Objective Optimization Method for Control Parameters of High-Speed Maglev Vehicle-Bridge System

A fast multi-objective optimization method (FMOOM) is proposed by optimizing control parameters to improve the dynamic performance of a high-speed maglev vehicle–bridge system. This approach involves generating the corresponding dynamic response to the sampled control parameters using a theoretical model of a high-speed maglev vehicle–bridge system, followed by establishing an adaptive surrogate model for the relationship between the control parameters and the dynamic response extrema. In the second step, we combine the adaptive surrogate model and the multi-objective gradient-based optimizer (MOGBO) algorithm to obtain the Pareto solution set satisfying different performance indexes. Additionally, the control parameters are optimized using the fuzzy comprehensive evaluation method. In the numerical simulation, we investigate five maglev trains and ten-span simply supported beam bridges and the theoretical model is verified by comparing the calculations with the measured results. The optimization effect of FMOOM is analyzed under different working conditions. The results show that the adaptive surrogate model has good prediction accuracy based on the radial basis function. Furthermore, the Pareto solution distribution of different schemes using FMOOM is reasonable, and the optimization results are as expected. Compared with the reference scheme, the dynamic response of the maglev vehicle–bridge system is smaller after being subjected to FMOOM optimization, and the six performance indexes are dramatically improved.

Development of polyurethane urea（PUU）– Waste rubber particles (WRP) composite materials for active ice-breaking of groove-filled asphalt pavement

The grooved-filled asphalt pavement has certain advantages in terms of pavement ice-breaking and anti-skid. However, the performances of the filling material limit its development. In this study, a polyurethane urea (PUU) - waste rubber particles (WRP) composite filling material was prepared by using a polyurethane (PU) and adding polyurea (PUa) with a similar microstructure as the cementing material, and adding WRP as the elastic reinforcing phase. The proportions of nine PUU-WRP composite materials were designed by changing the particle size and content of WRP, and then the filled composite materials were evaluated in terms of physical and mechanical properties, ice adhesion properties, interface bonding properties and aging resistance. The test results showed that the shore hardness, tensile strength, compression permanent deformation, and contact angle of PUU-WRP composite decreased as content of the WRP increased. Except the ice adhesion force results were the opposite. On the other hand, increased the WRP size resulted in increase in PUU-WRP composite’s shore hardness, compression permanent deformation, and ice adhesion force, while the tensile strength and contact angle were the opposite. The surface of the PUU-WRP composite material was hydrophobic, and the maximum contact angle was 102.3°. The reduction of WRP particle size and dosage was beneficial for reducing the ice adhesion force on the surface of PUU-WRP composite materials. The maximum interfacial shear and tensile strength of PUU-WRP composite material were 1.082 MPa and 0.244 MPa, respectively. After 42 days of UV aging, the maximum attenuation rate did not exceed 30 %. After the immersion test, the tensile strength attenuation of PUU-WRP composite material was basically controlled within 10 %. Finally, based on the fuzzy comprehensive evaluation (FCE) method, it was recommended to use WRP with a particle size of 0.6 mm and a dosage of 30 wt%-40 wt%.

Research on accident early warning of metallurgical enterprises based on grey DEMATEL/ISM and Bayesian network

To clarify the complex relationship between the factors causing safety accidents in metallurgical enterprises and predict the risk of accidents in enterprises, a correlation analysis model of the factors causing safety accidents in metallurgical enterprises based on grey Decision-Making Trial and Evaluation Laboratory/Interpretative Structural Modeling (DEMATEL/ISM) was established, and a Bayesian network early warning model was constructed on this basis. The relationship and action path of accident-causing factors in metallurgical enterprises were clarified. The factors were hierarchically divided and a multi-layer hierarchical structure model was established to obtain the neighboring cause, transitional cause, and essential cause of the accident. The results showed that the employee violation rate, the hazardous substances reserves, the toxic gas and dust pollution control compliance rate, the pass rate for equipment maintenance, and the qualification rate of special equipment were the neighboring causes of the accident. The perfection of the safety production management system was the essential cause. The Bayesian network early warning model was applied to the Fuxin Jiuxing Titanium work site. The expected risk probability of an accident was 17.9%, which was in a comparatively safe state (State2). The results obtained by the Bayesian model are consistent with those obtained by AHP and fuzzy comprehensive evaluation method, which proved the accuracy of the early warning model. The Bayesian model can give the risk probability value of the accident and the risk probability value of the accident cause factors at the same time, and include the causal relationship and conditional correlation relationship among the indicator variables in the reasoning process, which can provide targeted technical support for the construction of the emergency system of risk classification management and control.

Study on stability evaluation of goaf based on AHP and EWM—taking the northern new district of Liaoyuan city as an example

Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Driving mechanism of groundwater quality and probabilistic health risk quantification in the central Yinchuan Plain

The environmental changes from climatic, terrestrial and anthropogenic drivers can significantly influence the groundwater quality that may pose a threat to human health. However, the driving mechanism of groundwater quality and potential health risk still remains to be studied. In this paper, 165 groundwater samples were analyzed to evaluate the groundwater quality, driving mechanism, and probabilistic health risk in the central Yinchuan Plain by applying fuzzy comprehensive evaluation method (FCEM), redundance analysis (RDA) and Monte Carlo simulation. The results showed that hydrochemical evolution of groundwater were strongly influenced by water-rock interaction, evaporation and human activities. While 55.2% of groundwater samples reached the drinking water quality standard (Class I, II and III), 44.8% of samples exceeded the standard limits of Class III water quality (Class IV and V), indicating a high pollution level of groundwater. Mn, TDS, NH4+, NO3−, Fe, F−, NO2−, As were among major indicators that influence the groundwater quality due to the natural and anthropogenic processes. The RDA analysis revealed that climatic factors (PE: 10.9%, PRE: 1.1%), GE chemical properties (ORP: 20.7%, DO: 2.4%), hydrogeological factors (BD: 16.5%, K: 4.1%), and terrestrial factors (elevation: 1.2%; distanced: 5.6%, distancerl: 1.5%, NDVI: 1.2%) were identified as major driving factors influencing the groundwater quality in the study area. The HHRA suggested that TCR values of arsenic in infants, children and teens greatly exceeded the acceptable risk threshold of 1E-4, indicating a high cancer risk with a basic trend: infants > children > teens, while TCR values of adults were within the acceptable risk level. THI values of four age groups in the RME scenario were nearly ten times higher than those in the CTE scenario, displaying a great health effect on all age groups (HQ > 1). The present study provides novel insights into the driving mechanism of groundwater quality and potential health hazard in arid and semi-arid regions.

Research on Quality Evaluation of Innovation and Entrepreneurship Education in Colleges and Universities Under Big Data Environment

In innovation and entrepreneurship education, how to effectively use big data technology to improve the quality of education has become an urgent problem. In this article, the authors summarize the development of big data technology and its application background in higher education and point out the limitations of traditional education quality evaluation methods. They discuss the research status of the quality evaluation of innovation and entrepreneurship education in colleges and universities at home and abroad and the application of big data in education quality evaluation. Using the fuzzy comprehensive evaluation method, they constructed a quality evaluation model of innovation and entrepreneurship education in colleges and universities based on big data and proposed a corresponding evaluation process and index system. Finally, through empirical analysis, they verified the effectiveness and operability of the evaluation model. This research has theoretical and practical significance for improving the quality of innovation and entrepreneurship education in colleges and universities.

Towards efficient and accurate prediction of freeway accident severity using two-level fuzzy comprehensive evaluation

Accurately predicting freeway accident severity is crucial for accident prevention, road safety, and emergency rescue services in intelligent freeway systems. However, current research lacks the required precision, hindering the effective implementation of freeway rescue. In this paper, we efficiently address this challenge by categorizing influencing factors into two levels: human and non-human, further subdivided into 6 and 36 categories, respectively. Furthermore, based on the above factors, an efficient and accurate Freeway Accident Severity Prediction (FASP) method is developed by using the two-level fuzzy comprehensive evaluation. The factor and evaluation sets are determined by calculating the fuzzy evaluation matrix of a single factor. The weight matrix is calculated through the entropy method to compute the final evaluation matrix. Based on the maximum membership principle, the severity of the freeway accident is predicted. Finally, based on the experiments conducted with the traffic accident datasets in China and the US, it is shown that FASP is able to accurately predict the severity of freeway traffic accidents with thorough considerations and low computational cost. It is noted that FASP is the first attempt to achieve freeway accident severity prediction using the two-level fuzzy comprehensive evaluation method to the best of our knowledge.

Safety evaluation of human-caused errors in civil aviation based on analytic hierarchy process and fuzzy comprehensive evaluation method

PurposeAt present, the statistics of human error events in domestic civil aviation are limited, and the analysis indicators are difficult to quantify. The purpose of this study is to reduce the incidence of human error events and improve the safety of civil aviation.Design/methodology/approachIn this paper, a safety prevention evaluation method combining analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) is proposed. The risk factors of civil aviation safety are identified through questionnaire survey and calculated by MATLAB software.FindingsThe results of the study are as follows: a safety risk evaluation index system including 4 first-level indicators and 16 second-level indicators is constructed; the AHP is used to calculate the weight of the influencing factors of human error and sort them; and the FCE method is used to quantitatively evaluate the safety prevention of civil aviation human error and put forward the countermeasures.Research limitations/implicationsThis study also has some limitations. While it provides an overall quantitative identification of civil aviation safety risk factors, the research methods chosen, such as the questionnaire survey method and the AHP, involve individual subjectivity. Consequently, the research results may have errors. In the preliminary preparation of the follow-up study, we should analyze a large number of civil aviation accident investigation reports, more accurately clarify the human error factors and completely adopt the quantitative analysis method in the research method.Practical implicationsThis study identifies the risk factors of civil aviation safety and conducts a reasonable analysis of human error factors. In the daily training of civil aviation, the training can be focused on previous man-made accidents; in view of the “important” influencing factors, the aviation management system is formulated to effectively improve the reliability of aviation staff; according to the evaluation criteria of human error in civil aviation, measures to prevent and control accidents can be better formulated.Social implicationsIn view of these four kinds of influencing factors, the corresponding countermeasures and preventive measures are taken according to the discussion, so as to provide the basis for the prevention of aviation human error analysis, management and decision-making, prevent the risk from brewing into safety accidents and improve the safety of aviation management.Originality/valueBased on the questionnaire survey, this study creatively applies the safety prevention evaluation method combining AHP and FCE to the study of civil aviation human error, integrates the advantages of qualitative and quantitative methods, flexibly designs qualitative problems, objectively quantifies research results and reduces subjective variables. Then, by discussing civil aviation safety management measures to avoid risk factors, reduce the incidence of human error events and improve the safety of civil aviation.

Research on emergency decision quality evaluation and optimization basing on public sentiment big data analysis

The increasingly frequent occurrence of emergencies has led to significant losses, both human and economic. It is of the utmost importance to scientifically and effectively formulate emergency decision to prevent and reduce these losses. In this study, an evaluation model is developed for evaluating emergency decision quality based on fuzzy comprehensive evaluation method. The proposed model takes into consideration of the impact of public sentiment appeals on emergency decision in emergencies with the purpose of improving emergency decision quality. The “3·21” major explosion accident in Xiangshui County, Jiangsu Province, China, in March of 2019, is selected as a typical case, and the public sentiment big data is obtained from Weibo. The Latent Dirichlet Allocation (LDA) model and the TF-IDF algorithm are utilized to develop an emergency decision quality evaluation index system, from which public sentiment appeals are extracted and quantified. Furthermore, this study explores the changes of public sentiment attitude towards emergency decision through static and dynamic public sentiment analysis. Based on this, the emergency decision quality for the case event is evaluated by the proposed model. The effectiveness of the proposed approach is demonstrated with in-depth discussion and validation through this real case. The results indicate that the emergency decision quality of the Chinese government in this case is fairly good, yet exhibit room for further improvement. Optimization advice for emergency decision in emergencies is proposed accordingly. Empirical evidence suggests that the model proposed in this study can provide theoretical and methodological support for emergency response and government decision-making in the era of big data.

Wardrobe furniture color design based on interactive genetic algorithm

With the change in consumption environment and habits, the active feedback from users on online shopping platforms serves as a valuable source of information for analyzing user demand. Color design is an important factor in shaping product style and influencing user’s purchase decisions. This study combines the Latent Dirichlet Allocation (LDA) and an interactive genetic algorithm (IGA) to investigate the usability of the interactive genetic color selection method for wardrobe color design. Firstly, the LDA model was employed to cluster online review data to identify customer requirements (CRs), then summarize the perceptual evaluation factors (EFs) of color selection. Subsequently, the color selection information from market examples was used as reference to establish the initial population, and the interactive genetic color design process was completed with CorelDraw. Then, the fuzzy comprehensive evaluation method was employed to evaluate the color scheme generated from IGA. The empirical analysis demonstrated that the interactive genetic color selection method can effectively enhance both efficiency and satisfaction in wardrobe design. This study has substantial implications for both theory and practice in the field of wardrobe design and offers designers novel design concepts and methodologies.

Research on Comprehensive Performance Evaluation Method for Frontier Fundamental Research Project for Future Aircraft Engines

The evaluation and management of frontier fundamental research projects for future advanced aircraft engines are challenging due to the need to balance assessing the innovative potential and technical risks with considering their long-term effects and inherent uncertainties. This study presents a comprehensive evaluation indicator system for evaluating frontier fundamental research projects for future advanced aircraft engines, integrating the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation (FCE) to balance innovative potential with technical risks. The AHP is used to determine weights for the evaluation indicator system based on a survey of technical experts. By incorporating expert ratings and weighted criteria, the FCE method synthesizes comprehensive evaluations and effectively avoids traditional scoring biases and simplistic averaging methods. A case study on a major project is conducted to demonstrate the effectiveness of the proposed method in highlighting the significant achievements and potential for innovation gaps. The results show that the AHP-FCE method proves robust in identifying complex, prospective research, providing a strategic tool for policymakers to prioritize impactful aircraft engine research and ensuring investment in projects with significant breakthrough potential.

Research on the construction and application of a smart library services maturity evaluation system based on CMM

PurposeSmart libraries are the result of the application of smart technologies in the era of digital intelligence. The establishment and improvement of its service evaluation system serve as indicators for evaluating the growth of smart libraries.Design/methodology/approachThis study introduces and improves the capability maturity model (CMM), creatively constructs a service maturity model specifically designed for smart libraries and combines the Delphi method with the analytic hierarchy process (AHP) to establish a service maturity evaluation system for smart libraries while calculating indicator weights. Finally, two representative smart libraries are selected as case studies, and an empirical application is conducted using the fuzzy comprehensive evaluation method.FindingsThe empirical study shows that the developed smart libraries service maturity evaluation system holds significant theoretical and practical value in evaluating smart libraries.Originality/valueEnhances the CMM and creatively constructs a service maturity model for smart libraries. Combines the Delphi method with AHP to establish a service maturity evaluation system while calculating indicator weights. Uses a fuzzy comprehensive evaluation method to evaluate two representative smart libraries. Demonstrates that the smart library services maturity evaluation system holds significant theoretical and practical value.

RESEARCHING PUBLIC SATISFACTION IN SOCIAL GOVERNANCE THROUGH THE APPLICATION OF THE FUZZY COMPREHENSIVE EVALUATION METHOD

Social governance is an essential component of China's governance system and is the cornerstone of "Governance of China." In the new era, the Communist Party of China adopts the core value pursuit of "People-centered" as the rational choice for governing the country. "People-centered" is also the core concept of social governance in China. As participants in social governance, the satisfaction of the public is an important evaluation indicator for measuring the effectiveness of social governance. How to scientifically quantify and evaluate the satisfaction with social governance has always been a key issue in evaluating the effectiveness of social governance. This study constructs a scientific evaluation indicator system and uses the fuzzy comprehensive evaluation method to make a scientific evaluation of public satisfaction with social governance. This is also beneficial for carrying out other social governance work based on the evaluation results, thereby improving governance effectiveness.

Designing preschool children's educational games for enlightenment through decision analysis methods

As an innovative form of digital online education, educational games have potentially significant impacts on preschool children's enlightenment education. Identifying key factors for effective design is crucial in game development. This study identifies key factors for the design of educational games aimed at preschool children's enlightenment through decision analysis methods. The specific research steps include using SET analysis method to identify gaps in development opportunities, employing the Analytic Hierarchy Process to construct an interactive system design model for enlightenment educational games, calculating the weight value of each factor, and pinpointing the key factors for design practice. Based on this methodology, an enlightenment educational game has been developed, and Fuzzy Comprehensive Evaluation method has been utilized to assess the practical implementation. The approach outlined in this study enables designers to swiftly recognize the critical elements in designing educational games for preschool children's enlightenment, facilitating a responsive design process, achieving effective game designs, and ultimately enhancing preschool children's learning interest and outcomes.

Water chemical formation mechanism and water quality analysis of Shichuan River under the influence of human activities

ABSTRACT It is necessary to analyze the characteristics of the water environment and factors influencing the basin in order to determine its current ecological status. This study aims to investigate the chemical properties in the Shichuan River Basin using Gibbs diagram, Piper triangle diagram, correlation analysis, factor analysis, and main ion ratio method. The enhanced Nemerow comprehensive index method and fuzzy comprehensive evaluation method are employed for river water quality assessment. The findings reveal that runoff water has a weak alkaline nature with low salinity. The hydrochemical type of river water includes Ca2++Mg2++Na+-SO4 2-, Ca2++Mg2+-SO4 2-+Cl-+HCO3 -, Ca2++Na+-SO4 2-+Cl-+HCO3 -. Silicite and dolomite weathering are identified as primary influencing factors, while evaporite weathering also contributes to variations in chemical composition within the basin's waters. Ca2+, Mg2+, SO4 2- and HCO3 - originate from carbonate rock and silicate rock weathering processes, whereas Na+, K+ and Cl-, are primarily derived from evaporite weathering influenced by domestic sewage and agricultural activities. Agricultural production practices along with discharge of domestic sewage have an impact on Na+, K+, Cl- and NO3 -concentrations in aquatic systems. Water quality at all three monitoring sections falls under level IV classification. Phosphorus emerges as a key limiting factor for eutrophication within this basin's watersheds.

Evaluation of adaptability of software-defined telemetry systems for operational use

Abstract Aimed at solving the key problem of operational adaptability assessment of software-defined telemetry systems, the evaluation method of improved hierarchical method and fuzzy comprehensive evaluation is proposed. In the “general + expand + unique” flexible method to build an index system, the “expert decision matrix” index weight assignment and the fuzzy comprehensive evaluation method using operational adaptability assessment are used. According to the principle of maximum membership, the calculation results tend to be the largest. The proportion of 0.6524 shows that the equipment’s operational performance is good. At the same time, it was found that the proportion of qualified was 0.157, exposing its weaknesses and putting forward targeted suggestions, which provided a reference for the technical optimization and improvement, and forward-looking deployment of new equipment.

Optimal intensity measure for seismic performance assessment of shield tunnels in liquefiable and non-liquefiable soils

Relating the ground motion intensity measure (IM) and the structural engineering demand parameter is a crucial step in the performance-based earthquake engineering framework. This study investigates the selection of IM for development of probabilistic seismic demand model of urban shield tunnels subjected to earthquake ground motions in liquefiable and non-liquefiable soils. Nonlinear dynamic effective stress analyses are conducted to develop a database of the intensity measures and structural seismic responses exposed to ground shaking and soil liquefaction. Two advanced soil constitutive models (i.e., Pressure DependMultiYield03 and PressureIndependMultiYield for liquefiable and non-liquefiable soils, respectively) are employed to capture the nonlinear behavior. A suite of 23ground motion intensity measures is selected and assessed based on the evaluation criteria of correlation, efficiency, practicality and proficiency. Eventually, the multi-level fuzzy comprehensive evaluation method is employed to comprehensively consider the four evaluation criteria and establish the optimal ground motion IM suitable for probabilistic seismic demand analysis of shield tunnel structures. The obtained results show that the sustained maximum acceleration is the optimal IM for evaluating the structural seismic response, followed by the peak ground acceleration in both liquefiable and non-liquefiable soils. Peak pseudo velocity spectrum, displacement square integral and Housner spectral intensity are found to be not suitable for the probabilistic seismic demand analysis of shield tunnel structures.

Larval occurrence prediction of Dendrolimus punctatus based on fuzzy integrated evaluation method

AbstractTo improve the prediction accuracy of Dendrolimus punctatus larvae of overwintering, first and second generation and to provide a scientific basis for effective prevention and control of D. punctatus, six mathematical models of fuzzy comprehensive evaluation method were used to predict accumulative amount with the data of 1989–2014. The cumulative amount for the overwintering and the first generation was predicted in 2015, 2016, 2017, and 2018. The forecasted results of six models were all level 1, which was consistent with the actual results. Five forecasted results of six models and the actual results were level 1. The actual accumulative amount of D. punctatus for the second generation was level 1 in 2015, 2016, and 2017, which were consistent with the six models' forecasted results.

Objective Evaluation of Automatic Ambulance Performance and Weight Determination Through Analytic Hierarchy Process and Gray Correlation Theory

This paper proposes a comprehensive framework for testing and evaluating automatic ambulances, crucial for ensuring their reliability and safety in real-world scenarios. The framework includes designing test scenarios with varying complexity, covering environmental factors like road conditions, weather, and obstacles. An evaluation index system is introduced, comprising driving security, ride comfort, intelligence, and efficiency. Methodologies for calculating indicator weights, using the CRITIC and AHP methods, are presented to ensure fair evaluation. Additionally, evaluation methods including qualitative and quantitative techniques, such as grey correlation theory, are discussed. The test results show that the assessment results of the traditional fuzzy comprehensive evaluation method and the grey correlation theory evaluation method are highly consistent. The change in vehicle speed has less of an effect on accuracy during the real-time assessment process when the time interval is set to 0.1s, and the evaluation time of 0.098s can satisfy the requirement that the planning time of autonomous driving vehicles be shorter than 200 ms.