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dc.contributor.advisorJoseph, John E.
dc.contributor.advisorMargolina, Tetyana
dc.contributor.authorTanalega, Michelle
dc.date.accessioned2018-08-24T22:34:35Z
dc.date.available2018-08-24T22:34:35Z
dc.date.issued2018-06
dc.identifier.urihttp://hdl.handle.net/10945/59603
dc.descriptionApproved for public release. distribution is unlimiteden_US
dc.description.abstractAn unsupervised machine learning algorithm has been applied to passive acoustic monitoring datasets to detect and classify foraging calls of blue whales, Balaenoptera musculus, and fin whales, Balaenoptera physalus. This approach involves using a k-means clustering algorithm to cluster data based on common features, which produces a number of specified centroids. The centroids are then compared to machine-selected candidates for classification. Once divided into initial clusters, further clustering is done to fine-tune results. Preliminary testing of the algorithm yielded promising results. The cross-validation method and the DCLDE 2015 scoring tool were used to estimate out-of-sample performance of the detection algorithm. The automated detector/identifier has been applied to data collected during different seasons, and its performance was analyzed for various types of noise present in data, signal-to-noise ratios, and acoustic environment. The advantages of this approach over traditional manual scanning are increased reliable performance, and time and cost efficiency. This approach could potentially be a faster method of sorting and classifying large acoustic data sets.en_US
dc.description.urihttp://archive.org/details/applicationofmac1094559603
dc.publisherMonterey, CA; Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleAPPLICATION OF MACHINE LEARNING TECHNIQUES TO IDENTIFY FORAGING CALLS OF BALEEN WHALESen_US
dc.typeThesisen_US
dc.contributor.departmentOceanography
dc.subject.authormachine learningen_US
dc.subject.authork-meansen_US
dc.subject.authorbaleen whalesen_US
dc.subject.authorforaging callsen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Physical Oceanographyen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplinePhysical Oceanographyen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.identifier.thesisid27150


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