A Hybrid Model for Bankruptcy prediction Using Genetic Algorithm,Fuzzy C-Means and Mars

A. Martin · V. Gayathri · P. Gayathri

55 citations0/0 files storedInternational Journal on Soft Computing

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Artificial Intelligence in Healthcare Stock Market Forecasting Methods

Abstract

Bankruptcy prediction is very important for all the organization since it affects the economy and rise many social problems with high costs.There are large number of techniques have been developed to predict the bankruptcy, which helps the decision makers such as investors and financial analysts.One of the bankruptcy prediction models is the hybrid model using Fuzzy C-means clustering and MARS, which uses static ratios taken from the bank financial statements for prediction, which has its own theoretical advantages.The performance of existing bankruptcy model can be improved by selecting the best features dynamically depend on the nature of the firm.This dynamic selection can be accomplished by Genetic Algorithm and it improves the performance of prediction model. .

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 55 citations exist upstream.

References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1966Financial Ratios As Predictors of Failure 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 2002Credit scoring using the hybrid neural discriminant technique 1999Financial credit-risk evaluation with neural and neurofuzzy systems 2010A comparison of alternative bankruptcy prediction models 2001Forecasting Bankruptcy More Accurately: A Simple Hazard Model

Cited by

2015A Genetic Bankrupt Ratio Analysis Tool Using a Genetic Algorithm to Identify Influencing Financial Ratios 2015CROSS-COUNTRY STUDY ON THE DETERMINANTS OF BANK FINANCIAL DISTRESS 2012An analysis on business intelligence models to improve business performance 2015A reference model for business intelligence to predict bankruptcy 2013An Analysis on Qualitative Bankruptcy Prediction Rules using Ant-Miner

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.