Integration of incremental filter-wrapper selection strategy with artificial intelligence for enterprise risk management

摘要: The deterioration in enterprises’ profitability not only threatens the interests of those firms, but also means related parties (investors, bankers, and stakeholders) could encounter tremendous financial losses, which impact circulation limited economic resources. Thus, an enterprise risk forecasting mechanism is urgently needed to assist decision-makers adjusting their operating strategies so as survive under any highly turbulent climate. This research introduces a novel hybrid model that incorporates incremental filter-wrapper feature subset selection with statistical examination twin support vector machine (IFWTSVM) for performance forecasting. To promote model’s real-life application, knowledge visualization extracted from IFWTSVM represented easy-to-grasp style. experimental results reveal IFWTSVM’s quality very promising mining, relative other techniques examined this study.