원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.8 No.8
2015.08
pp.393-404
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, an efficient approach of combining additive expression tree model (AET) with hybrid evolutionary method is proposed to identify nonlinear systems. As linear variant of additive tree model, additive expression tree model is proposed to encode the mathematical formulations. For finding the optimal structure and parameters of systems, a hybrid evolutionary method integrating a new structure based evolutionary algorithm and cuckoo search is employed. We illustrate some experimental comparisons with neural network, neural network integrating fuzzy system and symbolic regression methods. Experimental results reveal that our model and optimization method perform better.
목차
Abstract
1. Introduction
2. Materials and Methods
2.1. Additive Expression Tree Model
2.2. Structure Optimization Methods
2.3. Parameter Optimization of Models using Cuckoo Search
2.4. Fitness Function Definition
3. Experimental Results and Illustrative Examples
3.1. Experiment 1
3.2. Experiment 2
4. Conclusion
Acknowledgements
References
1. Introduction
2. Materials and Methods
2.1. Additive Expression Tree Model
2.2. Structure Optimization Methods
2.3. Parameter Optimization of Models using Cuckoo Search
2.4. Fitness Function Definition
3. Experimental Results and Illustrative Examples
3.1. Experiment 1
3.2. Experiment 2
4. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보