大数据分析在安全事故预防中的技术实现与挑战  

The Technical Implementation and Challenges of Big Data Analysis in Safety Accident Prevention

作　　者：宋学刚 SONG Xuegang(Wudi County Xinxing Thermal Power Co.,Ltd.,Binzhou,Shandong Province,251900 China)

机构地区：[1]无棣县新星热电有限责任公司,山东滨州251900

出　　处：《大众科学》2024年第21期4-6,共3页China Public Science

摘　　要：探讨了大数据分析技术在安全事故预防中的应用,涵盖数据采集、存储、处理和分析等环节。重点阐述了基于机器学习的异常检测、预测模型构建和可视化决策支持系统的实现方案。同时分析了数据质量、算法优化、隐私保护等挑战,并提出解决策略。研究表明:大数据分析能提升事故预测准确性和预防效率,但仍需攻克多项技术难题。This study explores the application of big data analysis technology in safety accident prevention,covering data collection,storage,processing,and analysis.The implementation scheme of anomaly detection,prediction model construction,and visualization decision support system based on machine learning was emphasized.Simultaneously analyzed challenges such as data quality,algorithm optimization,and privacy protection,and proposed solutions.Research has shown that big data analysis can improve accident prediction accuracy and prevention efficiency,but multiple technical challenges still need to be overcome.

关 键 词：安全事故预防 机器学习 异常检测 预测模型 可视化决策 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]