@article{article_578494, title={MACHINE LEARNING APPLICATIONS IN OCEANOGRAPHY}, journal={Aquatic Research}, volume={2}, pages={161–169}, year={2019}, DOI={10.3153/AR19014}, url={https://izlik.org/JA92CP49XZ}, author={Ahmad, Hafez}, keywords={Machine learning,Oceanography,Application,Data driven}, abstract={<p class="MsoNormal" style="margin-top:6pt;margin-right:10.7pt;margin-bottom:3pt;margin-left:7.1pt;text-align:justify;"> <span lang="en-gb" style="font-family:’Times New Roman’, serif;" xml:lang="en-gb">Machine learning (ML) is
a subset of artificial intelligence that enables to take decision based on
data. Artificial intelligence makes possible to integrate ML capabilities into
data driven modelling systems in order to bridge the gaps and lessen demands on
human experts in oceanographic research .ML algorithms have proven to be a
powerful tool for analysing oceanographic and climate data with high accuracy
in efficient way. ML has a wide spectrum of real time applications in
oceanography and Earth sciences. This study has explained in simple way the
realistic uses and applications of major ML algorithms. </span> <span lang="en-gb" xml:lang="en-gb"> </span> <span lang="en-gb" style="font-family:’Times New Roman’, serif;" xml:lang="en-gb">The main
application of machine learning in oceanography is prediction of ocean weather
and climate, habitat modelling and distribution, species identification, coastal
water monitoring, marine resources management, detection of oil spill and
pollution and wave modelling. </span> </p> <p> </p> <p> </p>}, number={3}