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A knowledge-based risk management tool for construction projects using case-based reasoning

机译:基于知识的建筑项目风险管理工具,使用基于案例的推理

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摘要

Construction projects are often deemed as complex and high-risk endeavours, mostly because of their vulnerability to external conditions as well as project-related uncertainties. Risk management (RM) is a critical success factor for companies operating in the construction industry. RM is a knowledge-intensive process that requires effective management of risk-related knowledge. Although some research has already been conducted to develop tools to support knowledge-based RM processes, most of these tools ignore some critical features, such as live knowledge capture, web-based platform for knowledge sharing and effective case retrieval for learning from past projects. Moreover, several RM phases, such as risk identification, analysis, response and monitoring are not usually integrated. Thus, this study aims to bridge these gaps by developing a knowledge-based RM tool (namely, CBRisk) via case-based reasoning (CBR). CBRisk has been developed as a web-based tool that supports the cyclic RM process and utilises an effective case retrieval method considering a comprehensive list of project similarity features in the form of fuzzy linguistic variables. Finally, the developed tool was evaluated and validated by conducting black-box testing and expert review meeting. Results demonstrated that CBRisk has a considerable potential to enhance the effectiveness of RM in construction projects and may be used in other project-based industries with minimal modifications.
机译:建设项目通常被视为复杂和高风险的努力,主要是因为他们对外部条件的脆弱以及项目相关的不确定性。风险管理(RM)是建筑业经营公司的重要成功因素。 RM是一个知识密调的过程,需要有效地管理风险相关的知识。虽然已经进行了一些研究来开发工具以支持基于知识的RM进程,但大多数这些工具都忽略了一些关键特征,例如现场知识捕获,基于Web的知识共享平台和用于从过去的项目学习的有效案例检索。此外,通常不集成几个RM阶段,例如风险识别,分析,响应和监测。因此,本研究旨在通过通过基于案例的推理(CBR)开发基于知识的RM工具(即Cbrisk)来弥合这些差距。 Cbrisk已被开发为支持循环RM过程的基于Web的工具,并利用了考虑模糊语言变量的形式的项目相似性特征的综合列表的有效案例检索方法。最后,通过进行黑匣子测试和专家审查会议进行评估和验证开发工具。结果表明,CBRISK具有相当大的潜力,可以提高建筑项目中RM的有效性,并且可用于其他基于项目的行业,修改最小。

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