Translator Disclaimer
1 February 1994 Evaluating neural networks and artificial intelligence systems
Author Affiliations +
Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172504
Event: Substance Identification Technologies, 1993, Innsbruck, Austria
Abstract
Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David S. Alberts "Evaluating neural networks and artificial intelligence systems", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172504
PROCEEDINGS
12 PAGES


SHARE
Advertisement
Advertisement
Back to Top