Authors :
Ketan Bagade; Dr. Nikita Kulkarni; Dr. Vajid Khan
Volume/Issue :
Volume 8 - 2023, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/3497y9ne
DOI :
https://doi.org/10.5281/zenodo.8049727
Abstract :
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.
Keywords :
Business Failure, K Nearest Neighbors, Entropy Estimation, Long Short Term Memory, Decision Making.
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.
Keywords :
Business Failure, K Nearest Neighbors, Entropy Estimation, Long Short Term Memory, Decision Making.
