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Task decomposition and competing expert system-artificial neural net objects for reliable and real time inference

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2 Author(s)
R. Khosla ; Dept. of Comput. Sci. & Comput. Eng., La Trobe Univ., Bundoora, Vic., Australia ; T. S. Dillon

An integrated model for real time alarm processing in a real world terminal power station is applied. The integrated model is a combination of a generic neuro-expert system model, object model, and UNIX operating system process (UOSP) model. It is shown how the massive parallelism and fast execution features of ANNs help to cope with real-time system constraints like data variability and fast response time. For further enhancing reliability, a practical use of competing expert system-artificial neural networks (ES-ANN) objects is proposed

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Neural Networks, 1993., IEEE International Conference on

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