Modeling logic and neural approaches to bankruptcy prediction

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
Author/s:
  • Marín de la Barcena, Ámparo
  • Marcano Cedeño, Alexis Enrique
  • Piñuela Izquierdo, Juan Antonio
  • Andina de la Fuente, Diego
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

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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
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
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