Hanna Jeong, Youngsuk Kim
[Structural Equation Modeling of Health Promotion Behavior on Migrant Workers: A Multi-Group Analysis Based on the Period of Residence]
Journal of Korean Academy of Nursing
artificial intelligence ai proves decisive todays rapidly developing society motive force evolution financial technology subdivision artificial intelligence research machine learning ml algorithm extensively used aspects daily operation development supply chain using data mining deductive reasoning characteristics machine learning algorithms effectively help decisionmakers enterprises make scientific reasonable decisions using existing financial index data present globalization uncertainties covid19 intensifying supply chain enterprises facing bankruptcy risk operation process practical tools needed identify opportunely respond threat supply chain operation promptly predict probability business failure enterprises take scientific feasible measures prevent financial crisis good season artificial intelligence decisionmaking technology help traditional supply chains transform intelligent supply chains realize smart management promote supply chain transformation upgrading applying machine learning algorithms supply chain identify potential risks time adopt scientific feasible measures deal crisis also strengthen connection cooperation different enterprises advantage advanced technology provide overall operation efficiency account paper puts forward artificial intelligencebased corporate financialriskprevention frp model includes four stages data preprocessing feature selection feature classification parameter adjustment firstly relevant financial index data collected quality selected data raised preprocessing secondly chaotic grasshopper optimization algorithm cgoa used simulate behavior grasshoppers nature build mathematical model selected data sets selected optimized features support vector machine svm performs classification processing quantitative data reduced features empirical risk calculated using hinge loss function regular operation added optimize risk structure finally slime mould algorithm sma optimize process improve efficiency svm making algorithm accurate effective study python used simulate function corporate business finance risk prevention model experimental results show cgoasvmsma algorithm proposed paper achieves good results calculation found prediction decisionmaking capabilities good better comparative models effectively help supply chain enterprises prevent financial risks