DATA ANALYSIS MODEL OPTIMIZATION AND ARTIFICIAL POTENTIAL FIELD ALGORITHM FUSION APPLICATION IN THE INFORMATION SYSTEM
Volume 2, Issue 3, Pp 54-57, 2024
DOI: https://doi.org/10.61784/wjit3014
Author(s)
ZongYang Du
Affiliation(s)
Kwangwoon University, South Korea.
Corresponding Author
ZongYang Du
ABSTRACT
This paper discusses the fusion application of data analysis model optimization and artificial potential field algorithm in information system. This paper expounds the importance of data analysis in information system, and introduces the principle and characteristics of artificial potential field algorithm in detail. Through the research on the optimization method of data analysis model, the innovative idea of combining artificial potential field algorithm and data analysis model is proposed, including the strategy, step and technical realization of algorithm fusion. Analyze the fusion application in data clustering, path planning, abnormal detection of the advantages and effect, through the experimental comparison verified the effectiveness and superiority of the fusion method, to improve the ability of data analysis and intelligent level provides a powerful technical support and theoretical basis, has important application value and research significance.
KEYWORDS
Information system; Data analysis model; Optimization; Artificial potential field algorithm; Fusion application
CITE THIS PAPER
ZongYang Du. Data analysis model optimization and artificial potential field algorithm fusion application in the information system. World Journal of Information Technology. 2024, 2(3): 54-57. DOI: https://doi.org/10.61784/wjit3014.
REFERENCES
[1] Wang Rui. Analysis on the application of data analysis model of Shaanxi Agricultural specialty products. Fortune Today, 2024, (31): 8-10.
[2] Hao Shijia. Analysis of the index data of industrial enterprises in Jiangsu Province based on the optimization of the maximum information coefficient model. Communication and Information Technology, 2024, (05): 99-102.
[3] Xu Xiaojuan, Li Zongchao, Deng Mingchun, et al. Optimization method for transient thermal analysis model of high pressure turbine disk based on transition state test data. Aero-engine, 2024, 50(01): 57-63. DOI: 10.13477/j.cnki.aeroengine.
[4] Dong Bo, Luo Forest. Optimization and application of Text Semantic similarity Analysis Model in small datasets. Information Security Research, 2023, 9(10): 980-985.
[5] Chen Shuaishuai. Dimensionality reduction techniques and model optimization methods in big data analysis. Shandong University, 2023. DOI: 10.27272/d.cnki.gshdu.
[6] Fang Gang. Design and optimization of the energy efficiency analysis model of cement grouting construction quality based on data mining. And Jianghan University, 2023. DOI: 10.27800/d.cnki.gjhdx. 2023.000437.
[7] Shi Huijun, Liu Xianjun, Wang Zhigang. Evaluation of hydraulic expansion pipe: application of measurement data analysis and model optimization design. Chemical Equipment of China, 2023, 25(03): 3-8.
[8] Chen Huazhou. Quantitative analysis method of near-infrared spectroscopy and its application of agricultural informatization. Jinan University Press, 2022.
[9] Chang Fu. LIBS spectroscopy correction and model optimization method for rapid detection of high-temperature samples. University of Science and Technology Beijing, 2022. DOI: 10.26945/d.cnki.gbjku.
[10] Meng Lingming. Optimization of the plate shape control model for the unsteady process of hot continuous rolling based on data analysis. And Northeastern University, 2020. DOI: 10.27007/d.cnki.gdbeu.