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Automated implementation of rule-based expert systems with neural networks for time-critical applications
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Ramamoorthy, P. A. Huang, Song Govind, Girish |
| Copyright Year | 1991 |
| Description | In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed. |
| File Size | 1303436 |
| Page Count | 34 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19920005452 |
| Archival Resource Key | ark:/13960/t2n63fq64 |
| Language | English |
| Publisher Date | 1991-09-25 |
| Access Restriction | Open |
| Subject Keyword | Cybernetics Time Dependence Error Analysis Neural Nets Monitors Very Large Scale Integration Process Control Industry Manufacturing Expert Systems Rules Real Time Operation Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
