Proposal of Percolative Learning Method for the Baltic Dry Index Forecasting
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- Fuchikami Junko
- 商船三井システムズ株式会社 横浜国立大学大学院環境情報学府
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- Nagao Tomoharu
- 横浜国立大学大学院環境情報学府
Bibliographic Information
- Other Title
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- バルチック海運指数の予測に対する浸透学習法の提案
- バルチック カイウン シスウ ノ ヨソク ニ タイスル シントウ ガクシュウホウ ノ テイアン
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Description
<p>Japan depends on imports for almost all resources, which are supported by maritime trade. Since the shipping industry is a single global market and highly competitive, it is important to anticipate future fluctuations for stable transportation. On the other hand, existing research on time-series forecasting uses only past observations, making it difficult to predict future fluctuations more accurately. In this paper, we propose a training method of percolative learning model. We apply this method to test problems of predicting future shipping market. The results indicate that the proposed method is more accurate and effective than the conventional method.</p>
Journal
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- Journal of the Japan Society of Naval Architects and Ocean Engineers
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Journal of the Japan Society of Naval Architects and Ocean Engineers 33 (0), 199-207, 2021
The Japan Society of Naval Architects and Ocean Engineers
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Details 詳細情報について
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- CRID
- 1390570699998216320
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- NII Article ID
- 130008080998
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- NII Book ID
- AA12057769
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- ISSN
- 18811760
- 18803717
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- NDL BIB ID
- 031652167
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed