Earticle

초록

영어

Aiming at the cuckoo search algorithm (CSA) with disadvantages of slow convergence speed, getting into local extremum easily and low accuracy, we put forward cuckoo search algorithm with cauchy mutation(CCSA). For Bayesian networks(BNs) structure learning with insufficient data, we propose data completion method and Bayesian network structure learning with insufficient data based on CCSA(BNSL-ID-CCSA). In BNSL-ID-CCSA, firstly, we adopt K2 metric as evaluation measure for learning Bayesian networks from data. Secondly, we use expectation maximization(EM) algorithm and CCSA to make BNSL-ID-CCSA quickly and accurately converge to the global optimal solution. The experimental results show that BNSL-ID-CCSA has strong learning ability and good stability.

목차

Abstract
 1. Introduction
 2. Cauchy Mutation Suitable for CSA
 3. Cuckoo Search Algorithm with Cauchy Mutation
  3.1. Description of Cauchy Mutation on CCSA
  3.2. Description of CCSA
  3.3. CCSA Performance Analysis
 4. Bayesian Network Structure Learning with Insufficient Data Based on CCSA
  4.1. Data Completion in BNSL-ID-CCSA
  4.2. Description of BNSL-ID-CCSA
  4.3. BNSL-ID-CCSA Performance Analysis
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Wang Bo [ Computer Center, Qiqihar University, Qiqihar Heilongjiang 161006, China ]
• Zhang Jian-fei [ College of Computer and Control Engineering, Qiqihar University, Qiqihar Heilongjiang 161006, China ]
• Du Xiao-xin [ College of Computer and Control Engineering, Qiqihar University, Qiqihar Heilongjiang 161006, China ]
• Liu Yan-ju [ Computer Center, Qiqihar University, Qiqihar Heilongjiang 161006, China ]

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