2019년도 인터넷정보학회 추계학술발표대회
Current Result Document :
| 한글제목(Korean Title) |
Resilient Distributed Datasets을 기반으로 한 분포 추정 알고리즘 |
| 영문제목(English Title) |
An Estimation of Distribution Algorithm based on Resilient Distributed Datasets |
| 저자(Author) |
판더빈
이재완
덩창서
Debin Fan
Jaewan Lee
Changshou Deng
|
| 원문수록처(Citation) |
VOL 20 NO. 02 PP. 0273 ~ 0274 (2019. 11) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
In recent years, Spark has become a popular and common distributed computing framework, which has a resilient distributed datasets (RDD) support iterative computation. Evolving distributed parallel design on various types of evolutionary algorithm (EA) is an effective way to reduce the running time of the algorithm. In order to solve the continuous space optimization problems, this paper proposes an estimation of distribution algorithm based on resilient distributed datasets (RDEDA). The proposed RDEDA uses Gaussian probabilistic model to generate offspring in continuous space. And using Apache Spark's RDD model to implement parallelization of the proposed algorithm. The experimental results show that the proposed RDEDA has high accuracy and good scalability.
|
| 키워드(Keyword) |
|
| 파일첨부 |
PDF 다운로드
|
