fuzzy evaluation
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Electric vehicles have been promoted worldwide because of their high energy efficiency and low pollution. However, frequent charging safety accidents have to a certain extent restricted the development of electric vehicles. Therefore, it is extremely important to accurately evaluate the safety state of EV charging. The paper presents an integrated safety assessment method for electric vehicle charging safety based on fuzzy neural network. The integrated fault model was established by analyzing the correlation between truck–pile–grid. Then the integrated evaluation index was analyzed and sorted out, and the comprehensive fuzzy evaluation method used to evaluate. Following this, the improved GA_BP neural network algorithm was used to calculate the weight. Compared with the evaluation effect before and after the improvement, the simulation results show that the GA_BP neural network has higher accuracy and smaller error than the ordinary BP neural network. Finally, the feasibility and effectiveness of the evaluation method was verified by a case study.

In order to improve the accuracy of the teaching effect evaluation, a teaching effect evaluation model based on the intelligent fuzzy system is designed. The evaluation index are selected based on the teaching situation of physical education courses, relevant national policy documents, subject textbooks, intelligent fuzzy system to modify the index system through expert interview, determine the weight coefficient of each index by hierarchical analysis method (AHP), and calculate the single layer and total ranking of the index matrix to realize the evaluation of physical education courses. The test results show that the fuzzy evaluation accuracy of the proposed model is above 95.63%, with high evaluation performance and strong utility.

Abstract Urbanization and climate change usually result in frequent urban flooding. Since the floods cannot be avoided, the scenario simulation combined with risk analysis is an effective way to assess the disaster level and reduce direct damage loss when facing the emergency management problems. Different from the whole city dimension, the paper proposed a sub-catchment multi-index hesitant fuzzy evaluation model for the community planning level, and takes Jinjiang District of Chengdu city as the research object. Firstly, based on the PSR (Pressure-State-Response) model, the risk assessment system has been established in three aspects, including the current situation of urban drainage, the basic geographic information, and the social influence. Secondly, A total of 14 evaluation indexes were selected, among which the pressure index came from the calculation results of ArcGIS and EPASWMM5 model such as runoff coefficient, maximum water depth, etc. Thirdly, the expert hesitate fuzzy evaluation method was used to obtain the weight of 14 indexes of each sub-catchment. Finally, the 224 evaluation results were compared, and the urban flooding disaster risk map has been drawn. It is mainly concluded that 160 medium-higher risk areas were mainly concentrated in high built-up area in study area. Furthermore, the evaluation model is very useful as a decision-making tool for mitigation of the flood hazard and its associated risk.

Improvement in living standards has led to the development and utilization of forest green foods. The study seeks to examine the foundation and potential of forest green food industry in Yunnan Province. By constructing the industrial competitive advantage model, this paper measured and analyzed the competitiveness of forest green food industry in Yunnan Province from 2016 to 2020 by using fuzzy evaluation method and AHP. The conclusions were as follows: (1) The competitiveness of forest green food industry in Yunnan Province was at a medium level with competitiveness index of 83.98. (2) The competitive advantage of forest green food industry in Yunnan Province mainly depended on key factors such as natural endowment and education level. The area is however not having comparative advantage in general factors and important factors. Therefore, there is the need to put in place measures to realise the full potential of forest green food industry in the area by providing players in the sector with requisite skills.

Science and technology project evaluation is an important means of science and technology management. Whether the evaluation of science and technology projects is fair or not directly affects the development of national economy and the allocation of science and technology resources. Due to the complexity of the project and the fuzziness of human thinking, the expert information is often difficult to quantify in the process of project evaluation. Generally, the better choice is to express it in qualitative language. In this paper, the 2-tuple linguistic preference relation is proposed to evaluate scientific research projects. The reasonableness of the concept of complete consistency for the 2-tuple linguistic preference relation is discussed. Priority of 2-tuple linguistic preference relation is set up based on the 2-tuple weighted geometric averaging operator. Finally, combined with Science and technology project evaluation problem, the effectiveness and feasibility of the method are verified.

In recent years, badminton sports have attracted the public and the majority of young students. Badminton training has received extensive attention in the field of sports. However, there is currently no effective and accurate method for effective analysis of badminton training. In order to solve this problem, this paper combines the training teaching theory and the representation training theory and applies the fuzzy algorithm to construct the fuzzy evaluation model based on the analytic hierarchy process. After the experiment, the test scores of the sports quality of the two groups of badminton special students were improved. Through the screening of the seven functional modes of action, it was found that the special students’ left and right symmetry differences were obvious, the lower limbs were not stable, the core area was weak, and the muscle control ability on both sides of the spine needed to be strengthened.

In this paper a method that evaluates a trained artificial neural network is presented. The learning type of an artificial neural network is supervised learning which requires labeled input training vectors. Labeled medical data is provided to train the network, where the labels can either be 1 if the person is alive, or 0 if the person has deceased. The data is divided into training and validation vectors. The validation input vectors are used to evaluate the model and the results are summarized by using intuitionistic fuzzy values.

Increasingly, cities worldwide are striving for green travel and slow traffic, and vigorously developing people-oriented urban pedestrian traffic with sustainability has become a fixture in recent discourse. This paper comprehensively considers the sidewalk’s facilities environment and the status of pedestrian traffic flow; divides the urban pedestrian road system (UPRS) into five subsystems around the underpass, overpass, crosswalk, sidewalk, and road crosswalk; and introduces the basic structure as well as the function of each system. Then, the indicators are classified into two types of crosswalk facilities and sidewalk facilities, and a comprehensive pedestrian road indicator system with the combination of subjective and objective is established. Consequently, the integration of the fuzzy AHP and DEA-based symmetrical technique for the subjective evaluation indicator combined with pedestrian traffic characteristics is developed. A nine-step semantics scale of relative importance was used so that the symmetry of the response of pedestrian satisfaction was maintained. Fuzzy evaluation based on AHP is further modeled, and the DEA is employed to achieve an overall evaluation of the quality of service (QoS) for UPRS. The applicability of the established evaluation system is finally verified through a real case study in Harbin, China. The serviceability assessment method in this paper provides a new idea for planners to conduct sustainability evaluation for UPRS in future urban renewal development.

In modern conditions a comprehensive analysis of development trends and their effectiveness in various areas of human activity increasingly requires the analysis of data accumulated in numerous documents stored on the global network. Such an analysis is based on annual results in many areas of research, time trends and keywords. This analysis has certain peculiarities: it requires an analysis of not always accurate numerical information, comparison of qualitative indicators, obtaining both qualitative and quantitative characteristics, as well as the use of reference information for researchers and decision makers in related fields. In this regard, in recent years, a fuzzy assessment based on fuzzy mathematics is increasingly used in all types of assessing the effectiveness of various activities. The paper deals with conducting a bibliometric study based on the Extended Science Citation Index (SCI-E) and fuzzy performance measures to understand research trends and areas of focus. This paper takes the relevant scientific papers in Web of Science database as the research object, and analyzes the research trends with the help of bibliometrics. The results show that the number of papers published in the world is on the rise. The number of papers published in China and Iran is higher than that in other countries and regions. However, the number of papers cited in the United States and Turkey is higher than that in other countries or regions. Islamic Azad University is the largest. The research topics focus on fuzzy sets, fuzzy logic, genetic algorithms and performance evaluation. The research hotspots before 2011 included expert systems, neuro-fuzzy systems, and pattern recognition. After 2011, the research hotspots became neural networks, fuzzy sets, and machine learning.