Visualization is the process of transforming data, information, and knowledge into visual form, making use of humans’ natural visual capabilities. Different methodologies are available for analyzing large multidimensional data sets and providing insights with respect to scientific, economic, and engineering applications. This problem has traditionally been formulated as a non-linear mathematical programming. In this paper, we formulate the data visualization problem as a quadratic assignment problem. However, this formulation is computationally difficult to solve optimally using an exact approach. Consequently, we investigate the use of the genetic algorithm for the data visualization problem. To examine capabilities of proposed method, we use a demand database by electricity customers, and compare the results with results by Self Organizing Maps (SOMs). This can be concluded that this approach generates higher quality output.
목차
Abstract 1. Introduction 2. Literaturereview 2.1. Using linear equation to estimate nonlinear equation 2.2. Sammon’s Mapping (SM) 2.3.Multi-Dimensional Scaling (MDS) 2.4. Self-OrganizingMaps (SOM) 2.5. Discrete optimization 3. Modeling 4. Genetic algorithm 4.1. Chromosome representation and decoding 4.2. Selection 4.3. Crossover 4.4. Mutation 5. Case study 5.1. Visualization by using SOM 5.2. Visualization by using Genetic algorithm 6. Customer patterns classification 7. Conclusions References
키워드
Data VisualizationGenetic AlgorithmsData miningSelf Organizing Maps(SOMs).
저자
VahidGolmah [ Department of Computer Engineering, Azad University of Neyshabur ]
Jamshid Parvizian [ Isfahan University of Technology ]
보안공학연구지원센터(IJDTA) [Science & Engineering Research Support Center, Republic of Korea(IJDTA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Database Theory and Application
간기
격월간
pISSN
2005-4270
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Database Theory and Application vol.3 no.4