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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/2695

Title: A hybrid intelligent system to diagnose and indicate solutions to financial problems
Authors: Pacheco, Roberto
Martins, Alejandro
Weber, Rosina O.
Barcia, Ricardo M.
Khator, Suresh
Keywords: Hybrid Systems;Neural Network;Expert System;Financial Ratio;Financial Analysis
Issue Date: 4-Sep-1995
Citation: Paper presented at the First International Conference of Industrial Engineering (ENEGEP/95), San Carlos, Brazil.
Abstract: Monitoring and adjusting financial health problems play central role in the firm’s performance. Usually, small firms face difficulties in these tasks for lacking human resources and incapacity to afford a consultant. By analyzing the nature of the diagnosis and the solution of financial problems one can identify two different reasoning: during the diagnosis phase, the process is basically intuitive due to complex relations between financial ratios and problems; in the solution phase, the analyst follows a deductive approach searching for the causes and adjustments to the identified problem. Based on these aspects and on the motivation of providing a computational system to aid small firms, we built a Hybrid Intelligent System to diagnose (through Neural Network) and indicate solutions (through Expert System) to financial problems. In this paper we discuss the nature of the problems and present the system.
URI: http://hdl.handle.net/1860/2695
Appears in Collections:Faculty Research and Publications (IST)

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