Prediction of the Catch of Japanese Sardine Larvae in Sagami Bay Using a Neural Network
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- Komatsu Teruhisa
- Ocean Research Institute, University of Tokyo
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- Aoki Ichiro
- Ocean Research Institute, University of Tokyo
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- Mitani Isamu
- Kanagawa Prefectural Fisheries Experimental Station
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- Ishii Takeo
- Ocean Research Institute, University of Tokyo
書誌事項
- タイトル別名
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- Prediction of the Catch of Japanese Sar
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抄録
We attempted to forecast the catch of post-larval stages of Japanese sardine with total length 19-35mm exploited each year by troll and beach seine fisheries in Sagami Bay, Japan, during March and April. In the forecasting system, the feed forward (layered) type of neural network was utilized. The system for forecasting the catch in Sagami Bay during March and April was developed on the basis of (a) predicted hydrographic conditions (occurrence rates of the Kuroshio path types and distance between the axis and Cape Iroh-zaki in March and April) as predicted in the previous paper, (b) hydrographic data from November (previous year) to February (current year) and (c) Japanese sardine catch data in various landing regions in the previous year. The predicted values of catches agreed well with the observed catches. Upon investigation of the weights and threshold values in the trained neural network, the distance between the Kuroshio axis and Cape Iroh-zaki was found to significantly affect the predictions. We also examined how the data length for learning of the neural net affects the prediction. It appears that the neural network is a practical tool for predicting the catch.
収録刊行物
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- Fisheries science
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Fisheries science 60 (4), 385-391, 1994
公益社団法人 日本水産学会
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詳細情報 詳細情報について
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- CRID
- 1390282679406081792
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- NII論文ID
- 130003741901
- 40005348195
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- NII書誌ID
- AA10993718
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- NDL書誌ID
- 3644252
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- ISSN
- 09199268
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可