Estimate US Restaurant Firm Failure: The Artificial Neural System Model Versus Logistic Regression Model

Ravindra Patel

doi:10.55524/ijircst.2022.10.3.1

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.

Keywords

ANNs, Business, System, Model, Restaurant

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Cites this article as

R. Patel "Estimate US Restaurant Firm Failure: The Artificial Neural System Model Versus Logistic Regression Model", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-10, Issue-3, Page No-1-5, 2022. Available from: https://doi.org/10.55524/ijircst.2022.10.3.1

Corresponding Author

Ravindra Patel

Department of Computer Science, Campbellsville University, University Dr, Campbellsville, KY, USA

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