A distributed data collection system developed for use in cost sensitive situations is described. The system design constraints included reliability, low cost, high flexibility, and real time performance. The resulting system which evolved is a distributed expert system. Each node of the distributed system supports its own inference engine, scheduler and rule base with context sensitive switching between partitions and fact bases. Each node can support an artificial neural network (ANN).
1st New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems (ANNES 93), Dunedin, New Zealand, 24-26 November 2003, pp. 312-313
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