Earticle

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

키워드

저자

• Bin Yang [ School of Information Science and Engineering, Zaozhuang University, Zaozhuang, P.R. China 277160 ]

참고문헌

발행기관

간행물

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• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605