The Development of Software Teaching-Learning Model based on Machine Learning Platform

Park, Daeryoon; 대구서재초등학교,; Ahn, Joongmin; Jang, Junhyeok; Yu, Wonjin; Kim, Wooyeol; Youngkwon, Bae; Yoo, In Seol

doi:10.14352/jkaie.2020.24.1.49

Cited by 4 publications

(3 citation statements)

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“…Backpropagation refers to the loss error between the predicted value and the real value obtained last time. Starting from the output layer, Using the gradient descending method, the parameters of each layer are reversely corrected until the deviation between the actual loss and the actual loss of each layer is the target [21]. The specific operation steps are shown in Fig.…”

Section: B Improved Neural Network Algorithm Based On Genetic Algorithmmentioning

confidence: 99%

“…Formula (13), the initial population is M and the fitness of individual i is f i. After obtaining the probability of each individual, it will determine which individuals to mate with by random numbers between [0,1] Activities [21]. Since the interleaving mode has a great relationship with the actual coding situation, this article only discusses the coding method of floating-point numbers, and the form of arithmetic interleaving is as formula ( 14) [25].…”

Section: B Improved Neural Network Algorithm Based On Genetic Algorithmmentioning

confidence: 99%

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Research on Recommendation Model of College English MOOC based on Hybrid Recommendation Algorithm

Ding¹,

Jiang²

2023

IJACSA

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Establishing a reasonable and efficient compulsory education balance index system is very important to boost the all-around of compulsory education development, and then realize the course recommendation for students with different attributes. Based on this, the research aimed at the problems in college English education and evaluation, aimed to establish a college English MOOC education and evaluation system based on the improved neural network recommendation algorithm. The research first constructed the college English MOOC education and evaluation data elements, and then established a genetic algorithm improved neural network algorithm (BP Neural Network Optimization Algorithm Based on Genetic Algorithm, GA-BP), and finally analyzed the effect of the assembled model. These results show that the fitness of the GA-BP model reaches the set expectation when the evolutionary algebra reaches 10 times, and its fitness is 0.6. The corresponding threshold and weight are obtained, and the threshold and weight are substituted into the model. After repeated iterative training, the model finally reached an error of 10-3 when it was trained 12 times, and the expected accuracy was achieved. The R value of each set hovered around 0.97, and the fitting degree was high, which showed that the GA-BP model proposed in the study had a better fitting degree. The difference between the expected value and the output value is mainly distributed in the [-0.08083, 0.06481] interval. To sum up, the GA-BP model proposed in the study has an excellent effect on college English education and evaluation. This evaluation model has a faster learning rate and a higher prediction accuracy and more stable performance.

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Section: B Improved Neural Network Algorithm Based On Genetic Algorithmmentioning

confidence: 99%

Section: B Improved Neural Network Algorithm Based On Genetic Algorithmmentioning

confidence: 99%

Research on Recommendation Model of College English MOOC based on Hybrid Recommendation Algorithm

Ding¹,

Jiang²

2023

IJACSA

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show abstract

“…The main detection equipment that the underwater vehicle carries includes a sonar system, underwater camera system, and underwater lighting system. The control system is an embedded computer system processed by artificial intelligence, which mainly realizes the acquisition and monitoring of seabed targets [16]. According to the research on the classification of underwater biological types, the underwater vehicles shown in Figure 1b are equipped with high-resolution underwater cameras.…”

Section: Overview Of Neurorobotics and Related Principles Of The Mann...mentioning

confidence: 99%

Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education

Yang

Samsudin

Wang³

et al. 2023

Sustainability

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In order to realize the intelligence of underwater robots, this exploration proposes a submersible vision system based on neurorobotics to obtain the target information in underwater camera data. This exploration innovatively proposes a method based on the convolutional neural network (CNN) to mine the target information in underwater camera data. First, the underwater functions of the manned submersible are analyzed and mined to obtain the specific objects and features of the underwater camera information. Next, the dataset of the specific underwater target image is further constructed. The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. Furthermore, CNN is adopted to classify the underwater target images, which realizes the intelligent detection and classification of underwater targets. Finally, the model’s performance is tested through experiments, and the following conclusions are obtained. The model can recognize underwater organisms’ local, global, and visual features. Different recognition methods have certain advantages in accuracy, speed, and other aspects. The design here integrates deep learning technology and computer vision technology and applies it to the underwater field, realizing the association of the identified biological information with the geographic information and marine information. This is of great significance to realize the multi-information fusion of manned submersibles and the intelligent field of outdoor education. The contribution of this exploration is to provide a reasonable direction for the intelligent development of outdoor diving education.

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Meta-analysis on effects of artificial intelligence education in K-12 South Korean classrooms

Lee,

Kwon

2024

Educ Inf Technol

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The Development of Software Teaching-Learning Model based on Machine Learning Platform

Cited by 4 publications

References 0 publications

Research on Recommendation Model of College English MOOC based on Hybrid Recommendation Algorithm

Research on Recommendation Model of College English MOOC based on Hybrid Recommendation Algorithm

Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education

Meta-analysis on effects of artificial intelligence education in K-12 South Korean classrooms

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