Earticle

초록

영어

This paper concentrates on the issue of weather data mining. We propose a ARIMA algorithm based on Hadoop framework, and implement an effective weather data analyzing and forecasting system. We present the procedure to parallelize the ARIMA algorithm in the Hadoop environment, and construct a scalable, easy-to maintain, and effective weather forecasting system. Several experiments are conducted and results show that the proposed system is highly effective in terms of data storage, management, as well as query.

목차

Abstract
 1. Introduction
 2. Algorithm Design for the Forecast of ARIMA Model
  2.1. Algorithm Flow Chart
  2.2. Data Preprocessing
  2.3. Zero Transform Processing
  2.4. Stability Judgment
  2.5. Pattern Recognition
  2.6. Parameter Estimation
  2.7. Model and Forecast Evaluation Index
  2.8. Hadoop-based ARIMA Algorithm
 3. Experiment Design and Result Analysis
  3.1. The Weather Forecasting Platform
  3.2. The Establishment of a Data Set
  3.3. Experiment Design and Result Analysis
 4. Conclusions
 Acknowledgment
 References

키워드

저자

• Leixiao Li [ College of Information Engineering, Inner Mongolia University of Technology Huhhot, China ]
• Zhiqiang Ma [ College of Information Engineering, Inner Mongolia University of Technology Huhhot, China ]
• Limin Liu [ College of Information Engineering, Inner Mongolia University of Technology Huhhot, China ]
• Yuhong Fan [ College of Information Engineering, Inner Mongolia University of Technology Huhhot, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605