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Journals / Aquatic Research / 2019 / Cilt: 2 - Sayı: 3

MACHINE LEARNING APPLICATIONS IN OCEANOGRAPHY

Hafez AHMAD
Pages
161–169
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Machine learning (ML) is a subset of artificial intelligence that enables to take decision based on data.
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Key Findings & 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.
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Conclusion & Impact: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.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

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. 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.

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Cite This Article

AHMAD, H. (2019). MACHINE LEARNING APPLICATIONS IN OCEANOGRAPHY. Aquatic Research, Cilt: 2 - Sayı: 3, 161–169. https://ajindex.com/articles/143093

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