大数据背景下化工分析检验数据挖掘研究

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中图分类号：TQ014 文献标志码：A文章编号：1001-5922（2026）03-0795-04

Research on data mining of chemical analysis and inspection under the background of big data

CHEN Bangfu

（Rugao First Secondary Vocational School（Rugao Technician College），Nantong 2265Oo，Jiangsu China）

Abstract：Aiming at the problems of large data volume，fast generation speed，excessve types and low value density inchemical analysis and inspection data，as wellas the challenge that traditional data statistical processing methods can no longer process them，a data mining framework for chemical analysis and inspection under the background of bigdata isproposedandconstructed.First，theoverallframework isbuiltbyarchitecturaldesign，thenthecorealgorithmof thedata mining layer intheframework，namelytheBPneural network，isimprovedandoptimized，andfinally theeffectivenessand practicabilityof the data mining framework are verified through experimentsand tests. The test results show that the BP neural network model improved in this paper has the lowest MSE value in the test， with high predictionaccuracy，generalization abilityand stability，andcan beused as thecore algorithm of he data mining framework for chemical analysis and inspection underthe background of big data.Atthe same time，the data mining framework can discover potential laws from massive chemical inspection data，optimize the formulation of chemical materials，and provide strong support for the intelligent upgrading of the chemical industry.

Key words：big data;data mining;empirical data of chemical analysis;BP neural network ;particle swarm optimization algorithm

随着化工行业智能化转型不断加速，化工分析检验过程中产生了海量数据。（剩余4922字）