A framework for a real-time knowledge based system.
| dc.contributor.author | Gebbie, Ian | |
| dc.date.accessioned | 2018-07-19T08:19:36Z | |
| dc.date.available | 2018-07-19T08:19:36Z | |
| dc.date.issued | 1993 | |
| dc.description | A dissertation submitted to the Faculty of Engineering, University of the Witwatersrand, in fulfilment of the requirements of the degree of Master of Science Engineering | en_ZA |
| dc.description.abstract | A framework designed to contain and manage the use of knowledge in a real-time knowledge based system for high level control of an industrial process is presented. A prototype of the framework is designed and implemented on a static objectorientated shell. Knowledge is stored in objects and in forward chaining rules. The knowledge has a well defined structure, making it easy to create and manage. Rules are used to recognize conditions and propose control objectives. The framework uses the knowledge to determine variables that if altered will meet the objectives. Control actions are then found to implement changes to these variables The use of explicit control objectives makes it possible to determine if an action worked as intended and if its use is suitable for the present conditions. This enables a learning mechanism to be applied in the expert system. The prototype operated adequately, but the knowledge required to drive the. system was found to be very detailed and awkward to create. | en_ZA |
| dc.description.librarian | Andrew Chakane 2018 | en_ZA |
| dc.identifier.uri | https://hdl.handle.net/10539/25059 | |
| dc.language.iso | en | en_ZA |
| dc.subject | Expert systems (Computer science) | en_ZA |
| dc.subject | Real-time data processing. | en_ZA |
| dc.subject | Process control. | en_ZA |
| dc.title | A framework for a real-time knowledge based system. | en_ZA |
| dc.type | Thesis | en_ZA |
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