Intelligent semantic acquisition and smart decision support system of coal mine safety hazards
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摘要: 针对现有煤矿安全隐患智能语义采集与决策系统存在欠缺智能语义提取功能和多属性互联检索分析与决策功能、智能化程度不高等问题，设计了一种基于改进卷积神经网络（CNN）和蚁群算法（ACO)的煤矿安全隐患智能语义采集与智慧决策支持系统。该系统采用基于CNN的智能语义采集模型，利用CNN算法匹配出相似度最高的近义关键词，通过映射表关联到标准关键词，解决了相近语义的关键词匹配精度不高的问题；采用基于ACO的智慧检索模型，通过ACO算法负反馈和正向加强的方式标记高频度检索条例，实现了被检索的高频度条例的智能显示。实验与应用结果表明，该系统可实现多属性语义关键词的互联查询、高频度检索条例的智能显示、隐患问题相关数据的实时跟踪、数据统计图的多样化显示、决策分析预警简报的智能生成等功能。Abstract: In view of problems of lacking intelligent semantic extraction function and multi—attribute interconnection retrieval analysis and decision function，and low intelligence degree in existing intelligent semantic acquisition and decision system of coal mine safety hazards, a kind of intelligent semantic acquisition and smart decision support system of coal mine safety hazards based on improved convolutional neural network (CNN) and ant colony optimization (ACO) was designed. The system adopts CNN—based intelligent semantic acquisition model, and uses CNN algorithm to match the close semantic keywords with the highest similarity, and uses mapping table to concern the standard keywords, so as to solve problem of low matching accuracy of semantic keywords. The system adopts ACO—based intelligent retrieval model, and uses negative feedback and positive reinforcement method of ACO algorithm to mark high—frequency retrieval rules, so as to realize intelligent display of high—frequency retrieval rules. The experiment and application results show that the system can realize functions such as interconnection query of multi—attribute semantic keywords, intelligent display of high—frequency retrieval rules, real—time tracking of data related to hidden danger, and diversified display of data charts, intelligent generation of decision analysis and early warning reports.
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期刊类型引用(7)
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