Title
Integrating artificial neural networks with rule-based expert systems
Abstract
The Rule-Based (RB) and the Artificial Neural Network (ANN) approaches to expert systems development have each demonstrated some specific advantages and disadvantages. These two approaches can be integrated to exploit the advantages and minimize the disadvantages of each method used alone. An RB/ANN integrated approach is proposed to facilitate the development of an expert system which provides a "high-performance" knowledge-based network, an explanation facility, and an input/output facility. In this case study an expert system designed to assist managers in forecasting the performance of stock prices is developed to demonstrate the advantages of this integrated approach and how it can enhance support for managerial decision making.
Department(s)
Information Technology and Cybersecurity
Finance and General Business
Document Type
Article
DOI
https://doi.org/10.1016/0167-9236(94)90021-3
Keywords
Artificial neural network, Financial expert system, Hybrid expert system, Integrated expert system, Rule-based approach
Publication Date
1-1-1994
Recommended Citation
Yoon, Youngohc, Tor Guimaraes, and George Swales. "Integrating artificial neural networks with rule-based expert systems." Decision Support Systems 11, no. 5 (1994): 497-507.
Journal Title
Decision Support Systems
