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首页> 外文期刊>International journal of reliability, quality and safety engineering >Advances in Intelligent Expert Systems for Risk Analysis in a Complex Business Environment with Appropriate Solutions
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Advances in Intelligent Expert Systems for Risk Analysis in a Complex Business Environment with Appropriate Solutions

机译:Advances in Intelligent Expert Systems for Risk Analysis in a Complex Business Environment with Appropriate Solutions

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摘要

Today’s commonly used risk management procedures allow the planning team to focus on sensitive areas. It focuses the project team’s attention on activities and resources when a great risk threat exists or when the most time- and effective-engineering solutions can achieve expense reductions. Industrial security issues have worsened dramatically over the last decade. Over time, the risks in the sector rose as limited, single-train or batch operations shifted to massive multi-train operations. Often an accident leads to detrimental effects: shutting down the operation, loss of life, environmental disruption, and loss of business. The reparation of losses from the budget is unwelcome since the government’s reserve will not cope with these needs. This paper has a definitive comparative edge for company sponsors for project risk management (PRM) strategy. The sponsors who knowingly take chances, forecast unfavorable developments, defend themselves against unforeseen incidents and gain experience in price danger take the lead. However, this market benefit is largely dependent on the method to initially identify risks in the architecture of extensive multidisciplinary capital ventures. This paper explores how a sustainable market strategy works in reality. Using the market model, the business issues that need to be considered during the implementation or expansion of urban strategies are discussed. The PRM strategy shows a better-quality assurance ratio of 97.2, probability ratio of 95.3, safety rate of 97.5, reduced risk management rate of 22.6, an accident rate of 17.4, cost management of 25.1 and fuel consumption ratio of 23.7 when compared to existing strategies.

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