대한전자공학회:학술대회논문집 (Proceedings of the IEEK Conference)
- 대한전자공학회 2000년도 ITC-CSCC -2
- /
- Pages.1053-1056
- /
- 2000
Logical Combinations of Neural Networks
- Pradittasnee, Lapas (Faculty of Engineering Kimg Mongkut's Institute of Technology Ladkrabang) ;
- Thammano, Arit (Advaced Computer Application and Design Research Group Faculty of Information Technology, King Mongkut's Institute of Technology Ladkarbang) ;
- Noppanakeepong, Suthichai
- 발행 : 2000.07.01
초록
In general, neural networks based modeling involves trying multiple networks with different architectures and/or training parameters in order to achieve the best accuracy. Only the single best-trained neural network is chosen, while the rest are discarded. However, using only the single best network may never give the best solution in every situation. Many researchers, therefore, propose methods to improve the accuracy of neural networks based modeling. In this paper, the idea of the logical combinations of neural networks is proposed and discussed in detail. The logical combination is constructed by combining the corresponding outputs of the neural networks with the logical “And” node. The experimental results based on simulated data show that the modeling accuracy is significantly improved when compared to using only the single best-trained neural network.
키워드