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Study of Forecasting on Time Series Data by Nearest Neighbor Method.
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- Hanakuma Yoshitomo
- Department of Design and Computer Application, Miyagi National College of Technology
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- Yamamoto Junzou
- Technical Department, Idemitsu Engineering Co. Ltd.
Bibliographic Information
- Other Title
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- 最近隣法による時系列データ予測法の検討
- サイキンリンホウ ニ ヨル ジケイレツ データ ヨソクホウ ノ ケントウ
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Description
Methods of forecasting on time series data by auto-regressive model, neural networks model and chaotic theorem are proposed. The methods are said to be complicated for forecasting calculations. In this paper, a simple forecasting algorithm by the nearest neighbor method is discussed. It is applied to forecasting on a monthly average temperature in Sendai city to confirm performance. The actual results indicate that the nearest neighbor method has similar performance to the auto-regressive model in forecasting on time-series data.
Journal
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- KAGAKU KOGAKU RONBUNSHU
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KAGAKU KOGAKU RONBUNSHU 27 (2), 272-274, 2001
The Society of Chemical Engineers, Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390282679485003520
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- NII Article ID
- 10007819461
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- NII Book ID
- AN00037234
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- ISSN
- 13499203
- 0386216X
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- NDL BIB ID
- 5721361
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL Search
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed