Earticle

초록

영어

We applied simulated annealing algorithm and decision tree to find set of single nucleotide polymorphisms relevant to a disease and build a risk prediction model. For time complexity problem of simulated annealing caused by initial set and candidate generation, we constructed an initial set of the variants by fast heuristic algorithm and proposed a transition rules based on contribution of available variants. The experiment results show that we can obtain new set of variants with the reduced number of variants and the improved prediction performance compared to others by traditional feature selection algorithms.

목차

Abstract
 1. Introduction
 2. Background
  2.1 SNP
  2.2 Simulates Annealing (SA)
 3. Problem Definition
 4. Related Works
 5. Methods
  5.1 Speedup Strategy
  5.2 Transition Rule
  5.3 Temperature Scheduling
 6. Experiments and Results
  6.1 Data
  6.2 Evaluation Function
  6.3 Experimental Results
 7. Conclusion and Future Work
 Acknow;dgements
 References

키워드

저자

• DongHoi Kim [ Dept. of Computer Engineering, Hallym University ]
• Saangyong Uhmn [ Dept. of Computer Engineering, Hallym University ]
• Jin Kim [ Dept. of Computer Engineering, Hallym University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605