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

References

Alfaro, E., Garcia, N., Gam, M. and Elizondo, D. (2008). Bankruptcy forecasting: An empirical comparison of Ada Boost, and neural networks Decision Support Systems 4:110 – 122.
Gu, Z. (2002) Analyzing chapter 11 in the eatery business: various discriminant models. Universal Journal of Hospitality Management 21 (1): 25 – 42.
Hyewon Youn, and Zheng Gu. (2010). anticipate US eatery firm disappointments: The fake neural system show versus calculated relapse display. The travel industry and Hospitality Research, 10(3), 171. Recovered from http://0search.ebscohost.com.library.acaweb.org/login.aspx?direct=true&AuthType=ip,cpid,url&custid=s4338230&db=edsjsr&AN=edsjsr.23745462
Kim, H. what's more, Gu, Z. (2006a) A strategic relapse examination for anticipating chapter 11 in the accommodation business. The Journal of Hospitality Financial Management 14 (1): 17 – 34
O' Connor, R. (2002) Bolstering money ï¬‚ ow with key income the executives. Business Credit 104 (8): 42 – 44.
Opher T., Rom M., Kronaveter L., Friedler E., and Ostfeld A. (2012). A few perceptions on biofouling forecast in pipelines utilizing model trees and counterfeit neural systems versus strategic relapse. Urban Water Journal, 9(1), 11– 20.
National Restaurant Association (2008) Healthy children's dinners, neighborhood produce, smaller than expected pastries among most smoking menu patterns for 2009, http://www.restaurant.org/pressroom/official statement. Cfm? ID = 1708, got to 1 April 2009.
Ravi Kumar P., and Ravi V. (2007) Bankruptcy expectation in banks and ï¬rms by means of measurable and savvy strategies – A survey. European Journal of Operational Research 180 (1): 1 – 28
Robinson, R. (2008) United States: As restaurants falter, planning for restructuring, bankruptcy is crucial, http://www.mondaq.com/article .asp? Article id=69280, accessed 11 February 2009.
Wu, W., Lee, V. C. S. also, Tan, T. Y. (2006) Data preprocessing and information niggardliness in corporate disappointment conjecture models: Evidence from Australian materials industry. Accounting and Finance 46 (2): 327 – 345.
Youn, H. W., and Gu, Z. (2010) Predicting Korean hotel ï¬rm disappointments: An artiï¬cial neural system display alongside a calculated relapse demonstrate. Worldwide Journal of Hospitality Management 29: 120 – 127.
Zhang, G., Hu, M. Y., Cho (1994)., Patuwo B. E. what's more, Indro, D. C. (1999) Artiï¬cial neural frameworks in chapter 11 forecast: General structure and cross-approval examination. European Journal of Operational Research 116 (1): 6 – 32.

Cites this article as

[Ravindra Patel (2022), 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], (ISSN 2347 - 5552). www.ijircst.org

Corresponding Author

Ravindra Patel

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

Download Full Paper

Download PDF

No. of Downloads: 44 | No. of Views: 14997

Concurrent Data Processing in Microsoft Dynamics CRM Using Python

Akash Yadav, Jai Sehgal .

September 2023 - Vol 11, Issue 5
A Password and Least Significant Bit Substitution Based Steganography Technique for Image Hiding

Unmesh Mandal, Diotima Nag, Goutam Das, Rimpi Saha.

September 2023 - Vol 11, Issue 5
AI Based Food Quality Recommendation System

Aman Jatain, Shalini Bhaskar Bajaj, Priyanka Vashisht, Ashima Narang.

May 2023 - Vol 11, Issue 3

IJIRCST

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

Citations

Download Full Paper PDF

Total View 14997

Total Download 44