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  1. 401

    Big Data-Driven Macroeconomic Forecasting Model and Psychological Decision Behavior Analysis for Industry 4.0 by Jie Liu

    Published 2021-01-01
    “…The content of macroeconomic forecast is very extensive, and the existence of big data technology can provide the government with multilevel, diversified, and complete information and comprehensively process, integrate, summarize, and classify these pieces of information. …”
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    Analysis of College Students’ Physical Health Test Data Based on Big Data and Health Promotion Countermeasures by Ming Li, Fengcai Wang

    Published 2022-01-01
    “…In order to improve the data analysis and health promotion effect of college students' physical health test, this paper combines the big data technology to carry out the analysis and health promotion system of college students’ physical health test data. …”
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    Landscape Image Layout Optimization Extraction Simulation of 3D Pastoral Complex under Big Data Analysis by Juan Du, Yuelin Long

    Published 2020-01-01
    “…Finally, by introducing big data into the landscape layout optimization simulation, a layout optimization simulation method based on big data is constructed and used in the layout optimization simulation of the landscape image layout of the three-dimensional pastoral complex to guide the participatory layout optimization simulation.…”
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    Using Big Data Fuzzy K-Means Clustering and Information Fusion Algorithm in English Teaching Ability Evaluation by Chen Zhen

    Published 2021-01-01
    “…Aiming at the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, an English teaching ability evaluation algorithm based on big data fuzzy K-means clustering and information fusion is proposed. …”
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    Exploration of Flood Prediction in Watersheds Based on the Fusion Analysis of Remote Sensing Big Data with Multiple Physical Fields by Minming Xu, Yun Ouyang

    Published 2022-01-01
    “…The multiphysics remote sensing big data fusion analysis can divide the data into grids according to the grid method in the sliding time window, filter the normal data by information entropy in each grid, judge the remaining data that may be abnormal by using local abnormality factor, and eliminate the abnormal data according to the judgment result. …”
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