Abstract
This paper presents a neural-tuned neural network, which is trained by genetic algorithm (GA). The neural-tuned neural network consists of a neural network and a modified neural network. In the modified neural network, a neuron model with two activation functions is introduced. Some parameters of these activation functions will be tuned by neural network. The proposed network structure can increase the search space of the network and gives better performance than traditional feed-forward neural networks. Some application examples are given to illustrate the merits of the proposed network.
Original language | English |
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Title of host publication | IECON Proceedings (Industrial Electronics Conference) |
Pages | 2423-2428 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 1 Dec 2003 |
Event | The 29th Annual Conference of the IEEE Industrial Electronics Society - Roanoke, VA, United States Duration: 2 Nov 2003 → 6 Nov 2003 |
Conference
Conference | The 29th Annual Conference of the IEEE Industrial Electronics Society |
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Country/Territory | United States |
City | Roanoke, VA |
Period | 2/11/03 → 6/11/03 |
Keywords
- Genetic Algorithm
- Neural Network
- Pattern Recognition
- Sunspot Forecasting
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering