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• W2325610192 abstract "Soft sensors can predict values of a process variable y that is difficult to measure in real time. Adaptive mechanisms are applied to soft sensors to maintain their predictive ability. However, traditional adaptive soft sensors need a significant number of new y measurements. It is difficult to maintain the accuracy if the measurement interval is large. We propose two soft sensor models that produce accurate results with a small number of y measurements. We combined either a moving window technique or a just-in-time technique with a time difference model to handle changes of the slope between input variables X and y and shifts in X and y values. We analyzed a numerical simulation data set and a real industrial data set, demonstrating the superiority of the time difference model combined with a moving window technique." @default.
• W2325610192 created "2016-06-24" @default.
• W2325610192 creator A5082283686 @default.
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• W2325610192 date "2015-01-08" @default.
• W2325610192 modified "2023-10-03" @default.
• W2325610192 title "Moving Window and Just-in-Time Soft Sensor Model Based on Time Differences Considering a Small Number of Measurements" @default.
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• W2325610192 doi "https://doi.org/10.1021/ie503962e" @default.
• W2325610192 hasPublicationYear "2015" @default.
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