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- W2710993538 abstract "Abstract For continuous processes with slowly varying analog signals it becomes important to recognize in real time wether the actual situation of the process and/or the plant is similar or identical to a former situation. The reasons for the growing interest are discussed in the paper. To do situation recognition one introduces a time window, and the time series sampled from the analog process variables are shifted in discrete steps into this window. Within the time window process situations can be treated for recognition in different ways. Three strategies to do this are presented in the paper. For each strategy different ways of feature extraction and classification exist known from pattern recognition.A lot of these combinations have been investigated by simulations using an artificially defined synthetic process. One of this strategies was based on the ART2 neural network of Carpenter and Grossberg. Some of the many results of these simulations (hit and fault rates) are presented." @default.
- W2710993538 created "2017-06-30" @default.
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- W2710993538 date "1992-08-01" @default.
- W2710993538 modified "2023-09-25" @default.
- W2710993538 title "Approaches to Situation Recognition of Continuous Processes by Time Window and ANN Techniques" @default.
- W2710993538 cites W1757208074 @default.
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- W2710993538 doi "https://doi.org/10.1016/s1474-6670(17)49903-4" @default.
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