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ToolsKadlec, P. and Gabrys, B., 2008. Gating Artificial Neural Network Based Soft Sensor. In: Nguyen, N. T. and Katarzyniak, R., eds. New Challenges in Applied Intelligence Technologies. Berlin: Springer-Verlag, 193-202.
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Official URL: http://www.springerlink.com/content/t6l135078g1x74...
Abstract
This work proposes a novel approach to Soft Sensor modelling, where the Soft Sensor is built by a set of experts which are artificial neural networks with randomly generated topology. For each of the experts a meta neural network is trained, the gating Artificial Neural Network. The role of the gating network is to learn the performance of the experts in dependency on the input data samples. The final prediction of the Soft Sensor is a weighted sum of the individual experts predictions. The proposed meta-learning method is evaluated on two different process industry data sets.
| Item Type: | Book Section |
|---|---|
| ISBN: | 9783540793540 |
| Series Name: | Studies in Computational Intelligence |
| Issue: | 134 |
| Number of Pages: | 394 |
| Group: | Faculty of Science & Technology |
| ID Code: | 8500 |
| Deposited By: | INVALID USER |
| Deposited On: | 19 Dec 2008 19:06 |
| Last Modified: | 14 Mar 2022 13:19 |
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