Neural Networks as a Tool for Developing and Validating Business Heuristics
Document Type
Article
Publication Date
7-2001
Keywords
neural networks, heuristics, model selection, empirical evaluation
Digital Object Identifier (DOI)
https://doi.org/10.1016/S0957-4174(01)00024-0
Abstract
The increasing availability of information via the Internet and world-wide-web has made business decision-making more complex. Heuristic rules and methods are frequently used in complex domains to facilitate the decision-making process by reducing the amount of information that is required for decision-making. Heuristic rules may ‘go out of date’ as new information and new business methods are developed. Neural networks provide a fast and efficient means for evaluating the utility of existing heuristics. Two case studies are presented that demonstrate the use of neural networks for developing new heuristic rules or for refuting existing heuristic rules. Validation or adaptation of non-valid heuristics improves the quality of resulting business decisions.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
Expert Systems with Applications, v. 21, issue 1, p. 31-36
Scholar Commons Citation
Walczak, Steven, "Neural Networks as a Tool for Developing and Validating Business Heuristics" (2001). School of Information Faculty Publications. 202.
https://digitalcommons.usf.edu/si_facpub/202
