Earticle

초록

영어

Electronic circuit optimization design is important research field in engineering applications. Circuit scale and the time of evaluate the circuit are the challenge problems for circuit optimization design algorithm and the traditional optimization algorithms cannot solve the two problems very well. Cultural Algorithms are a class of computational models derived from observing the cultural evolution process in nature. Aiming at the disadvantages of basic Cultural Algorithms like being trapped easily into a local optimum, this paper improves the basic Cultural Algorithms and proposes the improved cultural algorithm (ICA) to solve the overcomes of the basic Cultural Algorithms. The new algorithm keeps not only the fast convergence speed characteristic of basic Cultural Algorithms, but effectively improves the capability of global searching as well. For the case studies, the new algorithm means has proved to be efficient and the experiment results show that the new means have got the better results.

목차

Abstract
 1. Introduction
 2. Basic Cultural Algorithm
 3. Improved Cultural Algorithm
  3.1. Adaptive cultural search operator
  3.2. Improved Influence Function
  3.3. Elite Selection Mechanism
  3.4. Experiment results
 4. Circuit Optimization Design Problem
  4.1. Circuit Representation 
  4.2. Circuit evaluation
  4.3. Circuit Optimization Design Case
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Xuesong Yan [ School of Computer Science, China University of Geosciences ]
• Qinghua Wu [ School of Computer Science and Engineering, Wuhan Institute of Technology ]
• Chengyu Hu [ School of Computer Science, China University of Geosciences ]
• Hong Yao [ School of Computer Science, China University of Geosciences ]
• Hanmin Liu [ Wuhan Institute of Ship Building Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605