Expanding the power of expert systems applications with neural networks
- Oak Ridge National Lab., TN (USA)
- Naval Academy, Annapolis, MD (USA)
It is well known that expert systems are useful in capturing expertise and applying knowledge to chemical engineering problems such as diagnosis, process control, process simulation, process advisory, etc. Traditionally, expert system applications are limited to knowledge domains that are heuristic and involve only simple mathematics. Neural networks however, represent an emerging technology capable of rapid recognition of patterned behavior without regard to mathematical complexity. Although useful in problem identification, neural networks are not very efficient in pointing to in-depth solutions and typically do not promote deep understanding of the problem or the reasoning behind its solutions. This paper explores the potential for expanding the scope of expert system applications by combining expert systems and neural networks. Specifically, this work demonstrates the use of knowledge that is pattern driven rather than heuristic and may be fuzzy, which is characteristic of many problems in chemical engineering. The feasibility of combining these two artificial intelligence (AI) technologies is explored through chemical engineering unit operations examples.
- Research Organization:
- Oak Ridge National Lab., TN (USA)
- Sponsoring Organization:
- DOE/ER
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 6680668
- Report Number(s):
- CONF-900828-6; ON: DE90016032
- Resource Relation:
- Conference: Summer national meeting of the American Institute of Chemical Engineers, San Diego, CA (USA), 19-22 Aug 1990
- Country of Publication:
- United States
- Language:
- English
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