Multiobjective Evolution of the Explainable Fuzzy Rough Neural Network With Gene Expression Programming

Cao, Bin; Zhao, Jianwei; Liu, Xin; Arabas, Jarosław; Tanveer, Mohammad; Singh, Amit Kumar; Lv, Zhihan

doi:10.1109/tfuzz.2022.3141761

Cited by 68 publications

(25 citation statements)

References 48 publications

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“…From the essential meaning of physical education curriculum, physical education curriculum reform should avoid the phenomenon of seeing "things" but not "people" and turn from strictly following the discipline characteristics of physical education to paying close attention to the theme needs of students. Physical education curriculum evaluation should follow the principle of "people-oriented" and build a scientific and reasonable new physical education curriculum quality evaluation system based on students as the main body, physical exercise as the main means, and improving health as the main goal and core [32,33]. Delphi method is used to establish and revise the curriculum quality evaluation index system.…”

Section: Evaluation Index Of Long Jump Training Coursementioning

confidence: 99%

“…From the perspective of data analysis, the content of this part is not included in the total score of the questionnaire. In the teaching quality evaluation questionnaire, the answer options of some questions involve very consistent (81-100), consistent (61-80), generally consistent (41-60), inconsistent (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40), and very inconsistent (0-20).…”

Section: Experimental Testmentioning

confidence: 99%

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Quality Evaluation Method of College Sports Long Jump Training Course Based on Genetic Algorithm

Han

Wang

Zhao

2022

Mobile Information Systems

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In order to improve the accuracy of the quality evaluation of college sports long jump training courses, this paper studies the quality evaluation method of college sports long jump training courses based on a genetic algorithm. According to the purpose of college long jump training course evaluation, basic principles of teaching quality evaluation and classroom teaching evaluation standards constructs the establishment process of evaluation index system and calculates the weight of long jump training course quality evaluation index based on AHP method, so as to provide index basis for subsequent quality evaluation; The quality evaluation model of the long jump training course is constructed based on the genetic algorithm. Through cross operation and mutation operation based on adaptive mutation probability, the high accuracy evaluation of college sports long jump training course quality is realized. The experimental results show that the evaluation accuracy of this design method is higher than 97.21%, and the evaluation satisfaction is higher than 97.15%, which significantly improves the accuracy of the university sports long jump training courses and has practical significance in the course evaluation.

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Section: Evaluation Index Of Long Jump Training Coursementioning

confidence: 99%

Section: Experimental Testmentioning

confidence: 99%

Quality Evaluation Method of College Sports Long Jump Training Course Based on Genetic Algorithm

Han

Wang

Zhao

2022

Mobile Information Systems

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“…The normality test is compared by the theoretical cumulative distribution function (CDF) of the data and the empirical distribution function(EDF) of the data (Ghasemi & Zahediasl, 2012), and a sample kolmogov-smirnov (KS) is used to test whether the data of the questionnaire are normal (Cao et al, 2022;Hew & Kadir, 2016;. The analysis is performed by testing observations for conformance to a normal distribution or other types by the nonparametric K-S statistic.…”

Section: Normality Testmentioning

confidence: 99%

Platformance-Based Cross-Border Import Retail E-Commerce Service Quality Evaluation Using an Artificial Neural Network Analysis

Feng

Chen

2022

Journal of Global Information Management

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The transaction scale of cross-border import e-commerce has grown rapidly around the world. Platform-style cross-border e-commerce does not control the quality, source and transaction process of goods strictly and comprehensively. In terms of customer service quality, the seller's customer service often ignores the customer's problems, and some customer service solutions cannot solve the customer's problems. Serving customers through the network has changed the traditional offline service form without distance, and the service process has a time and space distance. This paper constructs an evaluation index system based on the development of cross-border e-commerce. Through questionnaires, relevant data were obtained and analyzed. Analyze the results based on the collected data on the factors that affect the quality of cross-border import e-commerce services. Responsiveness is the most important factor found by artificial neural networks. The descending order of importance of other factors is fulfillment, diversity, privacy, reliability, compensation, and ease of use.

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“…ey surpass other techniques in terms of flexibility on the dataset and free assumption in the procedure. ere is no need for advanced statistical analysis prior to modeling [34][35][36]. By the use of ANN models, the patterns in the specification of problem and effective factors in an accident can be identified.…”

Section: Ann Approachmentioning

confidence: 99%

Application of Artificial Neural Network Approaches for Predicting Accident Severity on Rural Roads (Case Study: Tehran-Qom and Tehran-Saveh Rural Roads)

Habibzadeh

Ameri

Haghighi

et al. 2022

Mathematical Problems in Engineering

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Traffic accidents occur due to a combination of factors that lead to casualties and injuries. By identifying the most effective factors, it is possible for safety authorities to provide appropriate solutions for decreasing the accident severity and implementing preventive measures. The aim of this research was to present models to predict the accident severity on two-lane two-way (TLTW) rural highways in Iran over a one-year period from 2019 to 2020. Therefore, the occurrence probability of any type of accident was determined by artificial neural network (ANN)-based prediction models using nine independent variables affecting the accident severity. This study developed numerous ANN structures using back-propagation to model the potential nonlinear relationship between the accident severity and accident-related factors. Results indicated that among the models, the multilayer perceptron neural network (MLPNN) model with 6-2-2 partition had the best performance and prediction power. This model was developed using the standardized rescaling method for covariates and batch for training. Also, 9, 5, and 2 units were considered automatically for the input, hidden, and output layers, respectively, and the hyperbolic tangent and softmax were used as an activation function in the hidden and output layers, respectively. This model had the lowest cross-entropy error of 39.6 and the highest correct percentage of 82.5%, and the area under the receiver operating characteristic (ROC) curve was 0.852. Moreover, among all the effective variables, pavement condition index, roadside hazard, shoulder width, and passing zone ratio had the greatest impact on the accident severity. Finally, safety strategies were proposed to increase safety and reduce accidents along these roads.

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Multiobjective Evolution of the Explainable Fuzzy Rough Neural Network With Gene Expression Programming

Cited by 68 publications

References 48 publications

Quality Evaluation Method of College Sports Long Jump Training Course Based on Genetic Algorithm

Quality Evaluation Method of College Sports Long Jump Training Course Based on Genetic Algorithm

Platformance-Based Cross-Border Import Retail E-Commerce Service Quality Evaluation Using an Artificial Neural Network Analysis

Application of Artificial Neural Network Approaches for Predicting Accident Severity on Rural Roads (Case Study: Tehran-Qom and Tehran-Saveh Rural Roads)

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