Modeling landings profiles of fishing vessels: An application of Self-Organizing Maps to VMS and logbook data
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- 作者：Tommaso Russoa ; b ; Tommaso.Russo@Uniroma2.it" class="auth_mail" title="E-mail the corresponding author ; Paolo Carpentieric ; Fabio Fiorentinod ; Enrico Arnerie ; f ; Michele Scardia ; Alfonso Cioffig ; Stefano Cataudellaa
- 关键词：VMS ; Mé ; tier ; Self-Organizing Maps ; Neural networks
- 刊名：Fisheries Research
- 出版年：2016
- 出版时间：September 2016
- 年：2016
- 卷：181
- 期：Complete
- 页码：34-47
- 全文大小：5580 K
文摘
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Logbook data can be effectively combined with other data sources such as VMS.
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A SOM was trained on a large Italian logbook dataset for which VMS were available.
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SOM returned a pattern driven by fishing gears and ecology of the target species.
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The VMS-determined depth of fishing activities plays also an important.
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The trained SOM is also effective in predicting gear by landings profiles.