Fuzzy Comprehensive Assessment Research Articles

Developing a fuzzy comprehensive assessment model for English translation for college studentso

College students are learning a foreign language must know how to translate the spoken or written content from the respective language into English. These approaches do not help the college students to develop the capacity for rational thinking and adequate the motivation for the English translation. The educational principles are not in line with the qualities of the students in the typical English translation classroom teaching, and the teaching methods are out-dated. In the older process of the teaching English translation, many unreliable, vague aspects need to be considered, such as recognizing students’ fundamental English knowledge, unique circumstances, language proficiency, cultural differences, and the ambiguity of the source language. The main issue with the current English translation evaluation methodology is that it cannot be easily to deal with thecomplex fuzzy indices when judging the accuracy of the student translations. An algorithm named FCAM-AHP-ANFIS is proposed to provide an effective and accurate method for evaluating and predicting students’ English translation outcomes to overcome the traditional shortcomings. According to the proposed approach, students can learn about passive translation, but they may struggle to actively improve their translation skills. College students can benefit from the decision-making aid provided by the extensive evaluation technique due to its high availability and precision. The fundamental benefit of the fuzzy technique over more traditional forms of the assessment is that it accounts for the ambiguity and uncertainty of the making judgments at the human level and provides a coherent framework that includes the indistinct findings of the several steps in evaluating an English translation. The Fuzzy Comprehensive Assessment Model (FCAM) is a decision-making method that uses the fuzzy logic to assess the quality of English translations among the college students. The Analytic Hierarchy Process (AHP) is employed to calculate each criterion’s relative importance and determine the optimal weighting for each criterion utilized in the assessment model. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to analyze the translated data and generate predictions for the students’ translation outcomes. The experimental outcomes show the accuracy of the English translation assessment scores are 95.6% with 97% precision, 96% recall, and 96.5% of f1-score metric in addition to Root Mean Square (RMSE) and Mean Absolute Error (MAE).

Quantifying risks of lane-changing behavior in highways with vehicle trajectory data under different driving environments

Improper lane-changing behavior may have a great impact on the safety of the surrounding vehicles, and accurate risk assessment of lane-changing behavior can detect improper lane-changing behavior. Many existing risk assessment methods are based on the traditional minimum safe distance model as the theoretical foundation, not taking into account the effects of different weather and road conditions. Moreover, the initially calculated safe lane-changing distance through the model is generally the limit safety distance, which deviates to some extent from the initial distance maintained when the vehicle begins to change lanes during the actual driving process. The ratio of these two distances can reflect the degree of risk between the changing vehicle and its neighboring vehicles during lane-changing. For this reason, a lane-changing safety coefficient is defined and lane-changing risk assessment model based on the hyperbolic tangent function is constructed by combining the change characteristics of this coefficient. An environmental adjustment factor was introduced into the model to consider the influence of different driving weather and road conditions on the lane-changing risk assessment. Then, based on survey data from the survey questionnaire, the weights of the influencing factors were determined by using the hierarchical analysis method, and the environmental adjustment factor in the model was calibrated by using the fuzzy comprehensive assessment method. Finally, to verify the effectiveness of the model, the lane-changing trajectories of 373 vehicles were extracted from the HighD dataset. The risk assessment value of lane-changing was calculated by using the constructed model and was classified into high-risk, medium-risk and low-risk by using the K-means++ clustering algorithm. Various evaluation results were compared with the evaluation results from the expert evaluation method and the classical risk evaluation indexes, and the evaluation results are basically the same, which verifies the effectiveness of the lane-changing risk model established.

Assessment of child-friendly spatial environment in urban communities based on fuzzy Analytic Hierarchy Process

Urban development is progressively integrating the concept of child-friendly cities to foster inclusive and sustainable environments prioritizing children's needs and rights. This study contributes to the discourse on child-friendly urban spaces by leveraging the fuzzy Analytic Hierarchy Process (AHP) to assess these environments systematically. The methodology begins by compiling key factors influencing child-friendly environments. Using the AHP and expert scoring, judgment matrices are created to determine the weight of these factors, forming a structured assessment index system. The system is further refined through the development of specific rating items for each second-level factor, employing the fuzzy comprehensive assessment method integrated with membership functions. This approach enables a detailed, quantifiable analysis of factors contributing to child-friendly environments. To illustrate the practical application of this methodology, it was applied to Zengjiayan Community in Yuzhong District, a densely populated area of Chongqing, China, known for its mountainous terrain, thus navigating the distinctive challenges posed by this unique urban landscape. Extensive field research and interviews aligned second-level rating items with specific community features. Results yield a 'Good' rating for the community’s child-friendly environment, highlighting achievements and spatial constraints. These insights underscore the impact of urban design and policies on child-friendliness in challenging settings. The study provides a vital tool for urban planners and policymakers, presenting a model to assess and improve child-friendly spaces in complex urban settings.

The Strategic Positioning and Implementation Path of Red Cultural Resources in the Civic and Political Education Curriculum of Colleges and Universities

Abstract Red culture is an excellent cultural achievement formed by the Chinese leading people in long-term revolutionary practice, and it has become an indispensable content of ideological and political education in colleges and universities with its high value and rich connotation. Based on the strategic positioning of red cultural resources in the curriculum system of ideological and political education in colleges and universities, this paper designs the teaching path of red cultural, ideological, and political courses and implements it. It also constructs an assessment system to evaluate the quality of teaching in red culture and civic politics and proposes the use of the particle swarm algorithm to optimize the index assignment method in hierarchical analyses. Then, the fuzzy comprehensive assessment method is used to assess the teaching approach’s implementation effect. The implementation of the teaching path resulted in medium-high assessment scores for the teaching content, teaching method, and teaching effect, indicating the effectiveness of the red culture and civics teaching path. Students’ learning attitudes were significantly improved (3.5 points) compared with those before teaching (2.26 points), and it was found that the scores on the ideological and political quality test of the students who were taught with the integration of red resources were significantly higher than those of the traditional classes (P<0.05). This paper is critical for integrating cultural resources from the red minority into ideological and political education in colleges and universities.

Research on the Application Mode of Construction Engineering Safety Management Combined with BIM Technology

Abstract The advent of Building Information Modeling (BIM) technology heralds a new era in construction safety management. This research integrates BIM to forge a safety management system that proactively identifies construction risks and counteracts worker safety hazards in real-time. It also constructs a comprehensive BIM-based safety evaluation index, applying advanced multi-level fuzzy comprehensive assessment techniques and refined hierarchical analysis to calculate index importance. The study dissects safety management on multiple fronts through a detailed analysis of the construction safety practices at the new campus of People’s Hospital in Province A. The findings denote a basic level of success in collaborative safety efforts and an overall disappointing safety management score of 2.463, spotlighting an urgent need for systematic safety improvements within the project.

The influence of growth environment on college students’ mental health based on subjective and objective induction perspectives

Abstract The mental health of college students is closely linked to their upbringing environment. This study utilized a scale method to quantitatively assess family economic status, parenting styles, and closeness using subjective and objective induction perspectives. The survey data was obtained by combining Liket multipoint scoring, and the Cronbach’s alpha coefficient was utilized for testing. For the mental health assessment of college students, quantification and summation was conducted through fuzzy qualitative assessment, and the assessment criteria were established using the fuzzy comprehensive assessment method. The predictions were fitted using multiple linear regression after completing the descriptive statistical analysis and mediating role test. The family socioeconomic status factor was used to predict the mental health index of college students, which could reduce the error by 3.8%. The parenting style factor was used to predict the mental health index of college students, which could reduce 7.2% of the error. Using the factor of family closeness to predict the mental health index of college students can reduce the error by 4.2%. By exploring the influence of upbringing on mental health, psychological intervention methods can be better proposed.

Research on Performance Assessment of High Quality Development in Urban Green and Low Carbon Transformation

<p>In order to study the effective methods of green and low-carbon transformation in Chinese cities, this paper takes Rizhao City, Shandong Province, China, as the object of study. Based on the analysis of the research background and the literature review, and taking into account the characteristics of Rizhao City, the following five categories with a total of 25 indicators were selected to construct the assessment indicator system: the environmental quality of green and low-carbon transformation, the quality of the planning and construction of green and low-carbon transformation, the quality of the life and work in the green and low-carbon transformation, the quality of the process of the green transformation empowering the development of high-quality, and the quality of the results of the green transformation empowering high-quality development. Based on this, the two-level fuzzy comprehensive assessment model is reconstructed, and the relevant statistical data provided by the government is used to comprehensively assess the high-quality development performance of the green transformation and empowerment cities in Rizhao City from 2012 to 2022. It is found that the performance of high-quality development empowered by green transformation in Rizhao City, China, has shown a continuous upward trend, having risen from Level Ⅳ in 2012, to Level II by 2022, and remained at Level II during 2018-2022, with its assessment results and showing an upward trend. Finally, based on the specific research results, the policy suggestions to improve the high-quality development performance of cities empowered by the green and low-carbon transformation of Rizhao City, China are discussed.</p>

Safety Evaluation Method of Tunnel Construction System in Rechargeable Wireless Sensor Networks

In the aspect of constructing the comprehensive assessment and early warning model of typical risk of tunnel construction, this paper introduces fuzzy mathematics theory to quantify the typical risk factors of tunnel construction. On the basis of the constant weight of the warning index determined by Analytic Hierarchy Process (AHP), the variable weight calculation is added to establish a set of fuzzy hierarchical comprehensive assessment and early warning model of typical tunnel construction risks with variable weight, which further improves the accuracy and reliability of risk early warning. The cluster-based Rechargeable Wireless Sensor Networks (RWSN) on-demand charging method designed in this paper sends charging requests by cluster, and the Mobile Charger (MC) considers the distance from the requesting node as the priority criterion. Through the simulation, it can be seen that the algorithm proposed in this paper reduces the MC working energy consumption and improves the network performance. The dynamic risk index of construction process is obtained. The experimental results show that this method can track and analyze the dynamic risks in the construction process timely and accurately. By cooperating with the specific construction process, the probability of risk accidents is reduced and the safety of the project is ensured.

Evaluation of Energy Storage Station Based on the Optimal Weighting Method

The energy storage station is playing an increasingly important role in supporting new power systems. How to scientifically and effectively evaluate the application effect of energy storage stations is an urgent problem to be solved. In this study, a multi-indicator evaluation model for energy storage stations is established. An improved fuzzy comprehensive assessment (FCA) with optimal weight is applied to actual energy storage stations. Using the energy storage station monitoring platform, comprehensive evaluation scores of demonstrated energy storage stations are obtained. The support effect of energy storage stations on the power grid is evaluated from three aspects: performance, operational reliability, and energy efficiency. The higher the evaluation score, the stronger the energy storage regulation ability, and the more significant the active support to the power grid.

Satisfaction evaluation of a just energy transition policy: evidence from China

China has declared that it will achieve carbon neutrality by 2060, and energy transition will play a primary role in this process. This transition will encourage leapfrog development in efforts to achieve carbon neutrality. However, energy transition is often accompanied by social risks and injustices, which can be effectively addressed only by incorporating a just energy transition (JET) into the policy process. In this paper, three policy dimensions (material compensation, livelihood maintenance, and social development) associated with 13 policies designed to promote a JET in China are categorized. In addition, the satisfaction of vulnerable groups with these policy approaches is evaluated according to the analytic hierarchy process (AHP) and via second-level fuzzy comprehensive assessment (FCA). The results of a satisfaction evaluation of 1,329 vulnerable people who have been laid off, forced to immigrate, fallen into energy poverty, had their rights and interests violated, etc., indicate that the overall satisfaction rate with a JET is 0.404 (the total values of “very satisfied” and “satisfied”), i.e., less than half. Accordingly, China still faces clear JET challenges and should rely on the collaborative promotion of four multi-responsible actors: the government, enterprises and trade unions, social organizations, and individuals. Only through this process can social resources be widely absorbed and mobilized to foster cross-boundary discussions and ensure that no vulnerable populations are left behind. This study thus enriches policy research on energy transition, providing an opportunity to expand the academic horizon of JET as a research field. Furthermore, this study may also inspire policymakers to pay more attention to JET, offering references for subsequent policy improvement.

Modified analytic hierarchy process for risk assessment of fire and explosion accidents of external floating roof tanks

AbstractTo ensure the safe operation of external floating roof (EFR) tanks, it is important to conduct risk assessments for fire and explosion accidents. In this study, we develop a modified analytic hierarchy process to overcome the subjectivity in traditional analytic hierarchy analysis, improved analytic hierarchy process, and fuzzy fault tree analysis. We propose a parameter with a correction factor: the role of the parameter in the model can be gained from further modifying the structural importance of each basic event so as to overcome the subjectivity in traditional analytic hierarchy analysis, improved analytic hierarchy process, and fuzzy fault tree analysis. The judgment matrix for the analytic hierarchy process is constructed based on the modified structural importance of each basic event in a fault tree. The weight factor for each index to the top goal, combined with the fuzzy comprehensive assessment method, is adopted to conduct risk assessments for the fire and explosion accidents of EFR tanks.

An Approach to Managing Public Services that uses Big Data and Cloud Computing

Abstract: Governmental regulations have accelerated the development of information technology and resource grouping. One area of "digital gold" that is extremely practical and scientific is large-scale data mining. This is not simply a contemporary issue; it also calls for the rapid expansion of public service. As a result, it is possible to fully realise the advantages of information, improve service effectiveness, and close the service gap. Due to its speedy accounting, low memory requirements, and effective resource allocation, cloud computing has grown in popularity. Big data was therefore used in this work to analyse the current state of public cloud services, and fuzzy evaluation was used to analyse accurate monitoring. Eventually, the structure of the public service was enhanced, and a strategy for the precise organisation of the complete big data-driven public service process was created. According to a fuzzy comprehensive assessment, the design value and data entropy of public cloud services were increasing exponentially; the average design value of the accurate organisation for cloud-based government services was around 4.35, and the average significance of data entropy was around 0.98. Furthermore, big data-driven precision organisation of social public social welfare outperformed traditional precision monitoring of cloud-based services for the public, with results that suggested effects were 7% higher and overall capacity was 9% higher than the compared techniques.

Review of Launch Vehicle Engine PHM Technology and Analysis Methods Research

The reliability and safety of launch vehicle launch missions might be effectively increased thanks to the fault prediction and health management (PHM) technology of engines, which could also improve with problem diagnostics and decrease the cost of operation and maintenance overhaul. This paper combines the equipment characteristics and the current state of safeguarding for large, complex space systems, introduces the intelligent launch vehicle engine PHM technology methods that are being gradually implemented in space systems, and discusses and compares fault detection and health assessment techniques. Subsequently, analysis of the measurement signals from a rocket engine was performed using an example, and it was shown that the established comprehensive health assessment structure, which is based on the fault prediction algorithm method and the fuzzy comprehensive assessment method, could successfully realize the effectiveness of the rocket engine system health assessment, which had an outstanding application value.

An accurate management method of public services based on big data and cloud computing

Information technology and resource grouping are developing rapidly thanks to governmental policies. Large-scale data mining is a hugely practical and scientific zone of “digital gold”. This is not only a modern-day problem, but it also necessitates the rapid growth of service of publics. As a result, the benefits of information can be fully realized, service efficiency improved, and the service gap closed. Cloud computing has gained popularity due to its quick accounting, limited memory requirements, and efficient resource distribution. As a result, big data was employed to analyze the existing state of cloud-based service of publics in this paper, and the fuzzy evaluation process was used to analyze the accurate monitoring. Eventually, service of public organization was improved, and the path to the accurate organization of the entire service of public process initiated by big data was developed. The design value and data entropy of cloud-based services of public were growing exponentially, according to fuzzy comprehensive assessment; the value of average of the design value of accurate organization of cloud-based government services was around 4.35, and the average importance of data entropy was around 0.98. Furthermore, the organization control and detailed efficiency of big data-driven precision organization of social public social welfare outperformed traditional precision monitoring of cloud-based service of publics; suggesting that the effects were 7% higher, and overall capacity was 9% higher than the compared techniques.

Research on risk management and control strategy of uranium resource procurement in China

ABSTRACT As the scale of nuclear power in China continues to expand, the problem of external dependence on uranium resources has become more and more prominent. The guarantee of uranium resources is facing great risks, especially the procurement risks. Therefore, the procurement risks of uranium resources based on the analytic hierarchy process and fuzzy comprehensive assessment method from multiple perspectives is analyzed in this paper. The results show that the risk values of target region selection, supplier selection and uranium mining are 73.6, 71.3 and 71.8 respectively, which are the main risks. The risk values of procurement contract and procurement cost are 69.3 and 67.5, which are relatively low. They can be regarded as the secondary risks. In addition, the countermeasures of uranium resource procurement risk are put forward from six aspects including risk mitigation, risk prevention, risk transfer, risk avoidance, risk retention and risk backup measures. It is helpful to guide the risk management of China’s uranium resources in procurement and transportation activities

Research on Regional Basic Education Quality Assessment Based on Deep Convolutional Neural Network

At present, the informatization of basic education quality assessment has become a hot topic in the field of education and is playing an increasingly important role. Based on the theory of deep convolutional neural network, this paper adopts the methods of mathematical analysis and experimental research to construct a regional basic education quality assessment model. The model solves the data informatization problem of education quality assessment. In the simulation process, two key modules of data self-assessment and expert assessment of the deep convolutional neural network are realized by ASENET+SQL SERVER, and the assessment results are integrated by using the weighted average method and the fuzzy comprehensive assessment method. The experimental results show that the quantitative analysis of the quality assessment is carried out by using the logic and support relationship, and the results of comprehensive qualitative analysis and quantitative analysis are realized and segmented when the threshold level is 9, the MIOU obtains the highest value of 0.7501, and the MIOU of the multi-stage method of the quality evaluation model proposed in this paper is 0.8116, which is 6.15% points higher than the traditional multi-stage algorithm, which effectively improves the current stage area quality of basic education.

The Construction of University English Translation Teaching Model Based on Fuzzy Comprehensive Assessment

With the deepening of economic globalization, the communication between countries is getting closer and closer. The common topic of communication between people of different cultures and environments is English. Since the country has established English as a subject, the importance of English has become one of the main factors for the all-round development of students. In recent years, higher vocational education in China has once again developed towards high quality, all-round diversification, and innovation. According to the continuous reform and innovation and independent innovation, college English has been proved to be an important part of higher vocational education and an important measure to promote the development trend of higher vocational education all over the country. With the progress of science and technology and the development of economy, the level of education in China is still improving. People have put forward stronger teaching standards and regulations for English, a course with strong adaptability and practicality. Part of Chinese translation in college English shows its comprehensive ability and high-level thinking ability. In order to integrate this trend, this paper proposes the formulation and use of college English translation teaching model. The experiment proves that the accuracy of the traditional fuzzy evaluation method in the comment module design of college English translation teaching mode is low, only 82% at most. In order to solve this problem, BP optimization algorithm is introduced. The precision and reliability of BP optimization algorithm are improved. Because of the learning effect of the college English translation teaching mode based on the fuzzy evaluation BP optimization algorithm proposed in the certification paper, the certification is carried out according to the questionnaire and the final evaluation method. The students’ satisfaction and favoritism at the assessment level and the final results of their classmates have proved the proposed college English translation teaching model. The article has excellent learning effect.

Risk Assessment of an Existing Metro Tunnel in Close Proximity to New Shield Tunnels following Construction

The construction of a new shield tunnel near an existing operating tunnel poses a great risk to the existing tunnel structure due to the continuous encryption of the rail transit network. This study investigated the safety status of an existing metro tunnel in close proximity to new shield tunnels following construction. A fuzzy comprehensive assessment model (hierarchical fuzzy comprehensive evaluation model) based on an analytic hierarchy process was proposed to assess the risks of the existing tunnel structure. The threshold of indicators in the existing tunnel structure risk assessment system was determined based on the tunnel function and structure security. Then, we described the membership vector determination method, weight vector determination method, and comprehensive evaluation vector processing method. Taking a project case in China as the research object, the quantitative analysis of the established evaluation system was carried out, and the intuitive risk assessment results were obtained. The hierarchical fuzzy comprehensive evaluation model can be employed as a decision-making tool for newly built shield tunnels passing through the existing tunnels, which can provide guidance for tunnel maintenance and guarantee.

The Establishment of Risk Evaluation Index System for Small- and Medium-Sized Agency Bookkeeping Companies.

In recent years, China's economy has developed rapidly; many small companies have risen rapidly; and the tax system has become more and more standardized. Because many small businesses cannot afford to hire full-time accountants, they opt to outsource accounting services, giving small- and medium-sized bookkeeping firms a large market space. However, these opportunities also bring huge operational risks to small- and medium-sized bookkeeping companies. The purpose of this research is to help such enterprises carry out risk management and reduce operational risks. This study uses an analytic hierarchy process and a fuzzy comprehensive assessment approach to successfully combine quantitative and qualitative analysis and create a multilevel analysis structure model of the risk management evaluation index system of small- and medium-sized agency accounting firms. The structural model is verified by a case, the specific risk score of each factor is calculated through the scores of 20 experts, and the importance of risk is judged according to the size of the score, indicating that the structural model is feasible.

Information Security Risk Management Model for Big Data

In the current society of rapid expansion of information, big data have achieved vigorous development in all walks of life, considerably promoting data transmission and information sharing. Meanwhile, individuals are becoming increasingly reliant on big data and the Internet, but at the same time, the threat of information security posed by big data is becoming increasingly visible. As a result, how to protect the information security of big data has piqued the interest of both government and businesses. The essence of information security management is risk management, which is closely related to each other. Therefore, this study focuses on the following two aspects of research work. On the one hand, most existing risk management models merely describe risk management in the abstract from a macro-level, and they lack research on risk assessment, making them ineffective. This research builds a novel information security risk management model on the basis of existing risk management models based on the concept of multidimensional risk management. To achieve multidimensional dynamic management of big data risks and to keep them within an acceptable range as much as possible, the model is divided into five levels and two dimensions. On the other hand, this research also optimizes and improves the fuzzy mathematical analysis method and proposes a fuzzy comprehensive assessment method as the core algorithm for the risk assessment layer in the model. As a post-event risk assessment method, the advantage of this method is that it can comprehensively consider factors affecting risk and can quantify some assessment factors in the real network to achieve an effective combination of qualitative and quantitative, thereby providing a basis for decision-making in risk analysis and risk control. Finally, the effectiveness of the risk model in the real application is verified by example analysis, and it is intended that the study work would provide assistance and assurance for big data information security management.