Research on data mining algorithm based on neural network and particle swarm optimization

Fei, Xianju; Tian, Guozhong

doi:10.3233/jifs-169647

Cited by 16 publications

(6 citation statements)

References 8 publications

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“…In addition, there are still many data with low reference value, which brings great adjustments to data analysis. Faced with this situation, it is necessary to find valuable information contained in a large amount of data through data mining technology to improve the efficiency and accuracy of data analysis [12]. Genetic algorithm (GA) and particle swarm optimization (PSO) are two very commonly used data mining algorithms.…”

Section: Visual Aggregation Technology Based On Membershipmentioning

confidence: 99%

[Retracted] Construction of a Complex System Based on Big Data for the Intelligent Service System of Youth Physical Health

Song²,

Rochester

et al. 2021

Complexity

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The progress of social economy has created a better environment for the healthy development of young people, but the heavy schoolwork and life pressure have caused many students to ignore the scientific management of physical health. At this stage, people need a scientific physical health service system to help students understand their own health data, propose targeted exercise methods and health knowledge, and actively encourage and guide students to participate in physical exercise. The purpose of this article is to cultivate students’ good self-exercise awareness and improve their physical fitness and health. To this end, this article has designed a smart health service system for young people. This article introduces the various service functions in the health management service system and explains in detail the entry, induction, and analysis of student physical health data in the system. The essence of the health intelligent service system is to provide students with targeted healthy exercise strategies through data analysis. This paper studies the health intervention plan of the health intelligent service system. From the experimental data, the improved particle swarm algorithm in this paper increases the effectiveness of the system in adolescent health data mining from 80.5% to 92.19%, which undoubtedly optimizes the system. It helps a lot.

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Section: Visual Aggregation Technology Based On Membershipmentioning

confidence: 99%

[Retracted] Construction of a Complex System Based on Big Data for the Intelligent Service System of Youth Physical Health

Song²,

Rochester

et al. 2021

Complexity

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“…Nowadays, the computer network has become very popular in universities. Using DM technology to set up a university sports achievement management system can provide administrators, teachers, and students with sufficient information and quick query means, complete teachers' scoring work, and make statistics, analysis, and processing of data [3,4]. Wang et al used graduates' achievements as feature data, reduced the dimension of feature data by principal component analysis, and classified them by the Bayesian near k-nearest neighbor algorithm, namely, career direction prediction [5].…”

Section: Introductionmentioning

confidence: 99%

Construction and Effect Analysis of College Students’ Physical Education Teaching Mode Based on Data Mining Algorithm

Wang

2022

Journal of Sensors

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With the wide application of computer technology, communication technology, network technology, and multimedia technology in modern education, teaching methods tend to be diversified and scientific. Based on the DM (data mining) algorithm, this paper implements a sports achievement management system. Through this system, the efficiency of inputting and counting students’ achievements can be improved, and teachers can be freed from the complicated achievement management. Aiming at the problem that SVM (Support Vector Machine) is slow in training large sample sets in DM classification, a DM classification algorithm based on improved SVM, PSO_SVM, is proposed, which applies the density of adjacent samples to the design of membership function to reduce the influence of noise points on classification. The results show that the training time of this algorithm is increased by 54.26 s and 55.69 s compared with SVM and K -means, respectively, and the accuracy is increased by 35.62%. The results obtained by the DM algorithm will be helpful for teachers to diagnose teaching problems and construct PET (physical education teaching) model for college students with characteristics.

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“…Xianju Fei proposed a new hyperchaotic neural network image processing algorithm to generate real-time spatial position data stream in vehicle navigation. The results show that compared with other related algorithms, the algorithm has the advantages of strong stability and anti-interference, and is suitable for vehicle navigation in complex road conditions [11]. Xinyu Zhang proposed a panoramic vehicle image analysis algorithm.…”

Section: Introductionmentioning

confidence: 99%

Sparse representation optimization of Gaussian mixed feature of image based on convolution neural network

2022

Soft Comput

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With the rapid development of intelligent algorithm and image processing technology, the limitations of traditional image processing methods are more and more obvious. Based on this, this paper studies a new pattern of sparse representation optimization of image Gaussian mixture feature based on convolution neural network, and designs a sparse representation system model of vehicle detection image based on convolution neural network. The vehicle image data is collected from many aspects, and the convolution neural network is used for comprehensive analysis and evaluation. The model can extract the feature information of the vehicle detection image better by making the scheme of the real-time vehicle detection image and according to the image features and convolution neural network algorithm. The results show that the Gaussian mixture feature sparse representation optimization model based on convolution neural network has the advantages of high feasibility, high data accuracy and high response speed, which can enhance the processing efficiency of vehicle detection image and improve the utilization of local environmental information in the image.

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Research on data mining algorithm based on neural network and particle swarm optimization

Cited by 16 publications

References 8 publications

[Retracted] Construction of a Complex System Based on Big Data for the Intelligent Service System of Youth Physical Health

[Retracted] Construction of a Complex System Based on Big Data for the Intelligent Service System of Youth Physical Health

Construction and Effect Analysis of College Students’ Physical Education Teaching Mode Based on Data Mining Algorithm

Sparse representation optimization of Gaussian mixed feature of image based on convolution neural network

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