1 | Title of the Article | Estimate US Restaurant Firm Failure: The Artificial Neural System Model Versus Logistic Regression Model |
2 | Author's name | Ravindra Patel: Department of Computer Science, Campbellsville University, University Dr, Campbellsville, KY, USA |
3 | Author's name | |
4 | Subject | Computer Science |
5 | Keyword(s) | ANNs, Business, System, Model, Restaurant |
6 | Abstract | In view of recent years' financial information of US restaurant firms, this investigation created disappointment forecast models utilizing strategic relapse and artificial neural systems (ANNs). The discoveries demonstrate that the calculated model isn't inferior compared to the ANNs show as far as of forecast exactness. For restaurant firms, the strategic model not just gives bankruptcy prediction at a precision rate no inferior compared to that given by the ANNs demonstrate yet, in addition, shows how firms can act to lessen the opportunity of going bankrupt. Thusly, for US restaurant firms the strategic model is suggested as a favored technique for predicting restaurant firm disappointments. |
7 | Publisher | Innovative Research Publication |
8 | Journal Name; vol., no. | International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-10 Issue-3 |
9 | Publication Date | May 2022 |
10 | Type | Peer-reviewed Article |
11 | Format | |
12 | Uniform Resource Identifier | https://ijircst.org/view_abstract.php?title=Estimate-US-Restaurant-Firm-Failure:-The-Artificial-Neural-System-Model-Versus-Logistic-Regression-Model&year=2022&vol=10&primary=QVJULTgyOA== |
13 | Digital Object Identifier(DOI) | 10.55524/ijircst.2022.10.3.1 https://doi.org/10.55524/ijircst.2022.10.3.1 |
14 | Language | English |
15 | Page No | 1-5 |