An estimating method for missing data by using multiple self-organizing maps

Yuui Kikuchi, Nobuhiro Okada, Yasutaka Tsuji, Kazuo Kiguchi

研究成果: ジャーナルへの寄稿記事

3 引用 (Scopus)

抄録

In this paper, we propose a new method that uses multiple SOMs for estimating values lacking in data analysis. Recently, development of information technology grows the importance of data analysis. In actual data, however, some values will be sometimes missing, and then dealing with such insufficient data has become one of the important subjects in data analysis. Estimating and completing the empty values are required to applying various data analysis techniques. Such an estimation method is also applicable to data prediction problems. In the former methods that use SOM, many empty values would have caused the lack of data for learning process. Our system can achieve effective learning by using multiple SOMs even for data that includes many missing values. Moreover, the system is still available for nonlinear data because of using SOMs. We performed some numerical simulation using the proposed and other methods. By the simulation results, we showed the advantages of our method over some traditional techniques including a technique that uses single SOM.

元の言語英語
ページ(範囲)3465-3473
ページ数9
ジャーナルNihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
79
発行部数806
DOI
出版物ステータス出版済み - 12 6 2013

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Self organizing maps
Information technology
Computer simulation

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Mechanics of Materials
  • Industrial and Manufacturing Engineering

これを引用

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