Abstract:Based on random finite sets and random matrices, this paper conducts research on ETT methods, focusing on solving key problems such as measurement set division, hybrid reduction, and target shape modeling, and provides theoretical and methodological support for ETT applications in complex environments. Evaluation is an activity to determine value, which is to judge the degree to which the object meets the requirements of the subject, that is, to judge against certain standards. Usually, the evaluation needs to… Show more
“…The age of 3-6 is critical for developing young children's abilities. Whether it is from the ability of practical manipulation, divergent thinking, number perception, or music-sensitive perception, or the ability to work with rhythmic pleasing, or the ability to use colors, etc., are the characteristics that young children have at this stage [1]- [2]. Moderate interest development of young children is helpful for their growth [3].…”
To study the direction of preschool students’ interest development, this paper proposes to mine and analyze preschool students’ interest development data using a deep learning model. This paper first introduces the basic algorithmic process of deep learning BP neural network model, then uses a genetic algorithm to optimize the traditional BP neural network to get the best performance. The deep learning model is then used to analyze the preschool students’ family income, family structure, interest cultivation direction, gender and age, and interest cultivation orientation and diversion. The lower the family income, the higher the percentage of children choosing interest classes, mostly concentrated in families with income between 2000-8000. In terms of gender, there are also differences in interest cultivation analysis, with boys favoring the cultivation of science and sports abilities such as logical thinking, technology, calculation, and sports, accounting for about 20% more than girls in general, while girls favoring the cultivation of art abilities such as dance, English, reading, and vocal music, with 15-20% more than boys. Deep learning model-based interest development for preschool students can follow the natural choices of young children and provide scientific guidance for interest triage of preschool children.
“…The age of 3-6 is critical for developing young children's abilities. Whether it is from the ability of practical manipulation, divergent thinking, number perception, or music-sensitive perception, or the ability to work with rhythmic pleasing, or the ability to use colors, etc., are the characteristics that young children have at this stage [1]- [2]. Moderate interest development of young children is helpful for their growth [3].…”
To study the direction of preschool students’ interest development, this paper proposes to mine and analyze preschool students’ interest development data using a deep learning model. This paper first introduces the basic algorithmic process of deep learning BP neural network model, then uses a genetic algorithm to optimize the traditional BP neural network to get the best performance. The deep learning model is then used to analyze the preschool students’ family income, family structure, interest cultivation direction, gender and age, and interest cultivation orientation and diversion. The lower the family income, the higher the percentage of children choosing interest classes, mostly concentrated in families with income between 2000-8000. In terms of gender, there are also differences in interest cultivation analysis, with boys favoring the cultivation of science and sports abilities such as logical thinking, technology, calculation, and sports, accounting for about 20% more than girls in general, while girls favoring the cultivation of art abilities such as dance, English, reading, and vocal music, with 15-20% more than boys. Deep learning model-based interest development for preschool students can follow the natural choices of young children and provide scientific guidance for interest triage of preschool children.
The analysis of the current situation of skills and training strategies of preschool students in colleges and universities is to provide more professional talents for the cause of early childhood education. This paper first gives a brief description of the association rule mining algorithm under Internet technology, gives the evaluation method of association rules, including support, confidence, and enhancement, and gives the basic process of association rule mining. Next, it is explained that the multi-objective optimization problem utilizes the objective function optimization for calculating the optimal solution, and the commonly used multi-objective optimization problem solution and the selection method of the fitness function are given. Then the principle of the whale optimization algorithm is described and explained, the whale optimization algorithm is used to optimize the objective function of association rules, and then the steps and processes of the WOA-ARM algorithm are obtained. Finally, the algorithm was used to mine the training strategy of GZ University as an example, the “situational experience” teaching and training method was proposed, and the teaching characteristics and objectives of this method were analyzed. Regarding teaching objectives, 48.75%, 32.27%, 12.39%, and 6.59% of the ratings were A, B, C, and D, respectively. This indicates that the “situational experience” teaching training is suitable for college preschool students, and there is a strong correlation between the current skills and the training strategy.
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