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Integrated Multiple DEA Specifications and Visualization Technique for Advanced Management Analysis and Decision

机译:集成了多个DEA规范和可视化技术,用于高级管理分析和决策

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In recent years, financial troubles (such as, financial crisis, credit risk, and default) have begun to appear and continue to grow rapidly, which has shocked the confidence of stack market participants as well as has frozen the circulation of valuable economic resource. Most previous works only laid much more emphasis on well-examined studies, such as financial crisis prediction and credit risk prediction, the work on forecasting corporate operating performance that has been widely deemed as the main trigger for financial troubles is quite rare. To fill this research gap, we introduces an artificial intelligence (AI)-based hybrid architecture that integrated dominance-based rough set theory (DBRST), support vector machine with particle swarm optimization (SVM-PSO) and rule generation. The introduced model, tested by real-cases, is a promising alternative for corporate operating performance forecasting and it can assist in both internal and external market participants.
机译:近年来,金融麻烦(例如金融危机,信用风险和违约)开始出现并继续迅速增长,这震惊了堆栈市场参与者的信心,并冻结了宝贵的经济资源的流通。以前的大多数工作只把重点更多地放在经过严格审查的研究上,例如金融危机预测和信用风险预测,而被普遍认为是导致财务问题的主要诱因的预测公司运营绩效的工作却很少。为了填补这一研究空白,我们介绍了一种基于人工智能(AI)的混合体系结构,该体系结构集成了基于优势的粗糙集理论(DBRST),具有粒子群优化的支持向量机(SVM-PSO)和规则生成。引入的模型经过实际案例测试,是公司运营绩效预测的有希望的替代方法,它可以为内部和外部市场参与者提供帮助。

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