Szczegóły publikacji
Opis bibliograficzny
Classification of tea specimens using novel hybrid artificial intelligence methods / Paweł PŁAWIAK, Wojciech MAZIARZ // Sensors and Actuators. B, Chemical ; ISSN 0925-4005. — 2014 — vol. 192, s. 117–125. — Bibliogr. s. 124–125, Abstr. — Paweł Pławiak- dodatkowa afiliacja: Institute of Telecomputing, Faculty of Physics, Mathematics and Computer Science, Cracow University of Technology
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 78230 |
|---|---|
| Data dodania do BaDAP | 2014-01-09 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.snb.2013.10.065 |
| Rok publikacji | 2014 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Sensors and Actuators, B, Chemical |
Abstract
Two innovative systems based on feed-forward and recurrent neural network used for qualitative analysis has been applied to specimens of different fruit tea. Their performance was compared against the conventional methods of artificial intelligence. The proposed systems are a combination of data preprocessing methods, genetic algorithms and Levenberg-Marquardt (LM) algorithm used for learning feed forward and recurrent neural networks. The initial weights and biases of neural networks chosen by the use of genetic algorithms were then tuned with a LM algorithm. The evaluation was made on the basis of accuracy and complexity criteria. The main advantage of the proposed systems is the elimination of the random selection of the network weights and biases resulting in the increased efficiency of the systems. (C) 2013 Elsevier B.V. All rights reserved.
