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Modeling logic and neural approaches to bankruptcy prediction
Citation
Marín de la Barcena, Ámparo and Marcano Cedeño, Alexis Enrique and Piñuela Izquierdo, Juan Antonio and Andina de la Fuente, Diego (2010). Modeling logic and neural approaches to bankruptcy prediction. In: "2010 World Automation Congress", 19/09/2010 - 23/09/2010, Kobe, Japan. pp. 1-6.
Description
| Title: | Modeling logic and neural approaches to bankruptcy prediction |
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| Author/s: |
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| Item Type: | Presentation at Congress or Conference (Article) |
| Event Title: | 2010 World Automation Congress |
| Event Dates: | 19/09/2010 - 23/09/2010 |
| Event Location: | Kobe, Japan |
| Title of Book: | 2010 World Automation Congress |
| Date: | 2010 |
| Subjects: | |
| Freetext Keywords: | Bankruptcy Prediction; Artificial Neural Networks Applications; Risk Management |
| Faculty: | E.T.S.I. Telecomunicación (UPM) |
| Department: | Teoría de la Señal y Comunicaciones |
| Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
Abstract
The guiding principle of process automation and soft computing is to achieve more robust, traceable and low cost solutions which incorporate the required intelligence to information technologies, thus enabling human centered functionalities. The application of Artificial Intelligence (IA) and Neural systems to the financial and banking industries has performed well in the areas of Risk Management improvement and Bankruptcy prediction. This paper contributes to analyze the synergies between logic and neural based approaches as the basis to enhance bankruptcy prediction models development.
More information
| Item ID: | 65579 |
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| DC Identifier: | https://oa.upm.es/65579/ |
| OAI Identifier: | oai:oa.upm.es:65579 |
| Official URL: | https://ieeexplore.ieee.org/document/5665330 |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 12 Apr 2021 14:11 |
| Last Modified: | 10 May 2021 12:30 |
