Search results for "Fish school"

showing 3 items of 3 documents

Identifying small pelagic Mediterranean fish schools from acoustic and environmental data using optimized artificial neural networks

2019

Abstract The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of an…

0106 biological sciencesMarine conservationMaximum sustainable yieldFish stockFish school010603 evolutionary biology01 natural sciencesAcoustic surveyEnvironmental dataAnchovymedia_common.cataloged_instanceEuropean unionEcology Evolution Behavior and Systematicsmedia_commonEcologybiologySettore INF/01 - Informaticabusiness.industry010604 marine biology & hydrobiologyApplied MathematicsEcological ModelingEnvironmental resource managementPelagic zonebiology.organism_classificationClassificationComputer Science ApplicationsGeographyComputational Theory and MathematicsFishing industryModeling and SimulationbusinessNeural networks
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A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden

2022

The Svalbardsis one of the most intensively studied marine regions in the Artic; here the composition and distribution of marine assemblages are changing under the effect of global change, and marine communities are monitored in order to understand the long-term effects on marine biodiversity. In the present work, acoustic data collected in the Kongsfjorden using multi-beam technology was analyzed to develop a methodology for identifying and classifying 3D acoustic patterns related to fish aggregations. In particular, morphological, energetic and depth features were taken into account to develop a multi-variate classification procedure allowing to discriminate fish species. The results obta…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEnvironmental Engineering3D patternSettore INF/01 - InformaticaClusterEcological ModelingFish schoolMulti-beamK-meansSoftwareEnvironmental Modelling & Software
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Distribution and spatial structure of pelagic fish schools in relation to the nature of the seabed in the Sicily Channel (Central Mediterranean).

2009

Hydroacoustic data collected during two echosurveys carried out in the Sicily Channel in 1998 and 2002 were analysed to investigate the distribution and spatial structure of small pelagic fish species in relation to the sedimentological nature of the sea bottom. The study was carried out on two contiguous areas (labelled ZONE 1 and ZONE 2) of the continental shelf off the southern coast of Sicily, characterised by different dominant texture, ‘sand’ for ZONE 1 and ‘clayey-silt’ for ZONE 2. Simultaneous information on small pelagic fish schools and the seabed was obtained using a quantitative echo-sounder (SIMRAD EK500) that measures echoes due to the scattering from both fish schools and the…

geographygeography.geographical_feature_categoryacoustic surveySicily ChannelEcologyContinental shelffish schoolFishingPelagic zoneseabedAquatic ScienceSubstrate (marine biology)Demersal zoneEcho soundingOceanographyacoustic surveys; bottom and fish backscattering; echo-sounder; fish school; seabed; Sicily Channel.bottom and fish backscatteringGranulometryecho-sounderEcology Evolution Behavior and SystematicsSeabedGeology
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