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Early bankruptcy detection using neural network / Soh Rong Shu

EARLY BANKRUPTCY DETECTION USING NEURAL NETWORK_Soh Rong Shu_E3_2007_NI
Throughout the years, many researches have been conducted on the potential applications of Artificial Intelligence (AI) in bankruptcy detection. This project will provide an overview regarding the feasibility of the application of neural networks for direct classification of early bankruptcy detection based on financial ratio. A brief introduction to neural networks and the suitability algorithm of neural network for use in early bankruptcy detection determination will be investigated. In this project, several algorithm from Multilayer Perceptron network (MLP) will be developed and their performance are compared to yield the most suitable algorithm that will be used to model the classification system for determination early bankruptcy detection based on financial ratio. Among the types of algorithm that will be developed are Basic Gradient Descent (GD) algorithm, Levenberg-Marquardt (LM) algorithm, Bayesian Regularization (BR) algorithm, Scaled Conjugate Gradient (SCG) algorithm, Resilient Propagation (RP) algorithm and some more at Multilayer Perceptron network (MLP). This study proves that the Levenberg-Marquardt (LM) algorithm achieves the best performance as compared to the other algorithm. The Levenberg-Marquardt (LM) algorithm produces 84.85% accuracy. In this study, an intelligent system is developed for the classification of early bankruptcy detection using Levenberg-Marquardt (LM) algorithm. The proposed system provides several advantages in terms of its applicability, high accuracy, user-friendliness and as well as yields faster results compared to conventional system.
Contributor(s):
Soh Rong Shu - Author
Primary Item Type:
Final Year Project
Language:
English
Subject Keywords:
neural networks; Multilayer Perceptron network; detection determination
First presented to the public:
3/1/2007
Original Publication Date:
1/10/2018
Previously Published By:
Universiti Sains Malaysia
Place Of Publication:
School of Electrical & Electronic Engineering
Citation:
Extents:
Number of Pages - 91
License Grantor / Date Granted:
  / ( View License )
Date Deposited
2018-01-10 15:05:15.124
Date Last Updated
2019-01-07 11:24:32.9118
Submitter:
Nor Hayati Ismail

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Early bankruptcy detection using neural network / Soh Rong Shu1 2018-01-10 15:05:15.124