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Adast: a decision support approach based on an ontology and CBR. Application to railroad accidents

机译:Adast:基于本体和CBR的决策支持方法。应用于铁路事故

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摘要

Recently, an increasing number of companies and industries have undergone greatly in competition. At the same time, we are witnessing an explosion technological advances and new technologies of information and communication that companies must integrate to achieve the performance that goes far beyond those obtained by conventional practices. However, these constraints are at the origin of the birth of many risks. Sometimes we are witnessing serious and costly failures, accidents and human losses, especially when it is a highly risky area such as railroad transportation (our current case study). This paper aims at developing a decision support approach, called Adast. The approach adopted in this research is based on acquiring and reusing past accident scenarii, historically validated on other homologated transport systems. It is composed of two main parts: knowledge models described by an ontology, and a reasoning process based on case-based reasoning (CBR). In this article, we present the architecture of the approach, the case model, the key processes, and the first steps of the experimental validation through the model feasibility based on Adast.
机译:最近,越来越多的公司和行业经历了激烈的竞争。同时,我们正在见证爆炸性的技术进步以及信息和通信的新技术,公司必须整合这些技术以实现远远超出传统做法的性能。但是,这些限制是产生许多风险的根源。有时,我们目睹了严重且代价高昂的故障,事故和人员伤亡,尤其是在铁路运输等高风险地区(我们当前的案例研究)时。本文旨在开发一种称为Adast的决策支持方法。本研究中采用的方法基于获取和重用过去的事故场景,并在其他经过认证的运输系统上经过历史验证。它由两个主要部分组成:本体描述的知识模型和基于案例推理(CBR)的推理过程。在本文中,我们介绍了该方法的体系结构,案例模型,关键过程以及通过基于Adast的模型可行性进行的实验验证的第一步。

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