A Case Study for Software Quality Evaluation Based on SCT Model With BP Neural Network

Yan, Ben; Yao, Hua-Ping; Nakamura, Masahide; Li, Zhifeng; Wang, Dong

doi:10.1109/access.2020.2981872

Cited by 8 publications

(3 citation statements)

References 33 publications

(7 reference statements)

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“…One is the conversation model, which mainly investigates the interaction between teachers and students, between students and students, and between students and the environment through media [1,2] and examines the advantages and disadvantages of the virtual learning environment from the interactivity of various learning tools provided by online courses.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network

Jiang

Wang

2020

Complexity

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In the evaluation of teaching quality, aiming at the shortcomings of slow convergence of BP neural network and easy to fall into local optimum, an online teaching quality evaluation model based on analytic hierarchy process (AHP) and particle swarm optimization BP neural network (PSO-BP) is proposed. Firstly, an online teaching quality evaluation system was established by using the analytic hierarchy process to determine the weight of each subsystem and each index in the online teaching quality evaluation system and then combined with actual experience, the risk value of each index was constructed according to safety regulations. The regression model is established through BP neural network, and the weight and threshold of the model are optimized by the particle swarm algorithm. Based on the online teaching quality evaluation model of BP neural network, the parameters of the model are constantly adjusted, the appropriate function is selected, and the particle swarm algorithm which is used in the training and learning process of the neural network is optimized. The scientificity of the questionnaire was verified by reliability and validity test. According to the scoring results and combined with the weight coefficient of each indicator in the online course quality evaluation index system, the key factors affecting the quality of online courses were obtained. Based on the survey data, descriptive statistics, analysis of variance, and Pearson’s correlation coefficient method are used to verify the research hypothesis and obtain valuable empirical results. By comparing the model with the standard BP model, the results show that the accuracy of the PSO-BP model is higher than that of the standard BP model and PSO-BP effectively overcomes the shortcomings of the BP neural network.

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Section: Introductionmentioning

confidence: 99%

Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network

Jiang

Wang

2020

Complexity

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“…In the forward propagation process, the input information is processed layer by layer from the input layer through the hidden unit layer and then transmitted to the input layer. e state of neurons in each layer only affects the state of neurons in the next layer [16].…”

Section: Bpnn Principle and Improved Learning Algorithmmentioning

confidence: 99%

Research on Piano Informatization Teaching Strategy Based on Deep Learning

Hou

2022

Mathematical Problems in Engineering

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Applying information technology to piano teaching can effectively avoid these problems. The application of information teaching means can not only enrich teaching methods but also enhance students’ interest in learning. Deep learning (DL) focuses on immersing students in knowledge and learning situations, emphasizing critical thinking, and realizing the intrinsic value of knowledge. Understanding DL theory is of great significance to deepening the teaching reform in China. BP algorithm is a very effective algorithm for prediction and evaluation. In this paper, the complex factors affecting the quality of piano information teaching are comprehensively considered, and the improved BP neural network (BPNN) algorithm is used to evaluate and predict the quality of piano information teaching. The model structure of BPNN for evaluating and predicting the quality of piano information teaching is given and simulated in MATLAB. The results show that the evaluation and prediction method overcomes the subjective factors of expert evaluation and obtains reasonable results. Compared with the traditional BPNN algorithm, it has good applicability.

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“…The above expression suggests that the output expected will be between zero and one or 0% and 100%. Figure 3 represents a typical structure of neural networks (Yan et al, 2020). even in the mapping of any complex function (Peng, 2021;Youjun & Liu, 2010;Du, 2018).…”

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confidence: 99%

Modelling Financial Variables Using Neural Networking to Access Creditworthiness

Ubarhande,

Chandani,

Pathak

et al. 2024

Financial Internet Quarterly

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This study examines the existing credit rating methodology proposed in the literature to explore the development of a new credit rating model based on the financial variables of the enterprise. The focus is on the period after the financial crisis of 2018. This study aims to develop a credit rating model using neural networking and tests the same for its accuracy. The goal of this study is to address the issue brought up by previous research on subjectivity in the data used to determine creditworthiness. The database for the study includes financial data up to July 2022 from December 2018. A model is created to assess an enterprise's creditworthiness using neural networking. This study first evaluated the existing credit rating models proposed in the literature. Next, based on financial data and neural networking, a model is developed. It was evident that the model developed in this study has an accuracy of 85.16% and 76.47% on train and test data respectively. There exist several models to determine the creditworthiness of borrowers but all failed to address the concern of subjectivity in the data. The model created in this study made use of cutting-edge technology such as neural networking and financial data. This paper's unique approach and model construction based on a comparison of existing models is rare in the literature and justify the originality of this paper with a practical value at the global level.

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A Case Study for Software Quality Evaluation Based on SCT Model With BP Neural Network

Cited by 8 publications

References 33 publications

Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network

Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network

Research on Piano Informatization Teaching Strategy Based on Deep Learning

Modelling Financial Variables Using Neural Networking to Access Creditworthiness

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