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Intelligent System for Prediction of Sensor Drift
| dc.contributor.author | Golovko, V. | ru |
| dc.contributor.author | Savitsky, Y. | ru |
| dc.contributor.author | Sachenko, A. | ru |
| dc.contributor.author | Kochan, V. | ru |
| dc.contributor.author | Turchenko, V. | ru |
| dc.contributor.author | Laopoulos, T. | |
| dc.contributor.author | Grandinetti, L. | |
| dc.coverage.spatial | Brest | ru |
| dc.date.accessioned | 2021-07-27T08:09:27Z | |
| dc.date.available | 2021-07-27T08:09:27Z | |
| dc.date.issued | 1999 | |
| dc.identifier.citation | Intelligent System for Prediction of Sensor Drift / V. Golovko [and etc.] // International Conference on Neural Networks and Artificial Intelligence ICNNAI'99 = Международная конференция по нейронным сетям и искусственному интеллекту ICNNAI'99 : Proceedings, Brest, Belarus, 12–15 October 1999 / Brest Polytechnic Institute, Department of Computers and Laboratory of Artificial Neural Networks, Belarus Special Interest Group of International Neural NetWork Society, International Neural NetWork Society, Belarusian State University of Informatics and Radioelectronics (Belarus), Belarusian Academy of Sciences, Institute of Engineering Cybemetics (Belarus), Universidad Politechnica de Valencia (Spain), Institute of Computer Information Technologies (Ukraine, Ternopil) ; ed. V. Golovko. – Brest : BPI, 1999. – P. 126–135. | ru |
| dc.identifier.uri | https://rep.bstu.by/handle/data/20646 | |
| dc.description.abstract | ln this paper the features of neural networks using for improve of measurement accuracy of physical quantities by sensor drift prediction are considered. There is use a technique of data volume increasing for training of predicting neural network by using of separate approximating neural network. | ru |
| dc.language.iso | en | ru |
| dc.publisher | BPI | ru |
| dc.title | Intelligent System for Prediction of Sensor Drift | ru |
| dc.type | Научный доклад (Working Paper) | ru |
