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Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

机译:基于案例推理和可变模糊集的公路建设安全预警研究

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摘要

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.
机译:作为涉及建设项目的高风险子行业,公路建设安全在过去20年中经历了重大发展,这主要是由于中国建设项目缺乏安全预警。通过将预警技术的现状与国家安全生产监督管理总局的要求相结合,运用基于案例的推理技术,阐述了基于案例推理的公路建设安全预警的概念和流程。本研究通过使用关联规则挖掘,支持向量机分类器以及可变的模糊定性和定量变化准则模式,为索引选择,事故原因关联分析和预警程度预测实施这三个关键问题提供了解决方案。安全预警系统的需求。通过对每种方法的原理和优点的详细描述,并通过证明这些方法在安全预警应用中的有效性和协同作用能力,建立了安全的公路建设预警系统的有效手段和智能技术。

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