Info: Zenodo’s user support line is staffed on regular business days between Dec 23 and Jan 5. Response times may be slightly longer than normal.

Published June 17, 2023 | Version v1
Journal article Open

Business Failure Prediction through Deep Learning

Description

During the course of carrying out company
operations, complications might often arise as a result of
turbulent business operating circumstances and
unforeseen abnormalities. In most cases, a number of
difficulties combine to cause a lengthy decrease in the
project's perceived usefulness or collapse owing to a
depletion of financial resources. Preemptive evaluation of
a company's failure may help anticipate potential
challenges and mitigate the negative effects of such
challenges by methodically planning, preparing, and
carrying out a business failure prediction. For an
accurate forecast of the collapse of a company, it is
important to do a prediction analysis of the activities of
the firm in order to detect potential problems. Methods of
machine learning or deep learning that can be used for
the goal of generating an accurate forecast of the collapse
of a firm may effectively be used to identify these issues,
and they can be used to do so successfully. This
methodology will be realized by the successful use of the
method of K-nearest Neighbor Clustering as well as
entropy estimation, in conjunction with Long-Short Term
Memory and Decision Making.

Files

IJISRT23MAY722.pdf

Files (487.3 kB)

Name Size Download all
md5:9fc6bec616b78e8f7fa8567a1b1654cb
487.3 kB Preview Download