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Sensors 2017, 17(10), 2225; https://doi.org/10.3390/s17102225

A Machine Learning Approach to Argo Data Analysis in a Thermocline

College of Computer Science and Technology, Jilin University, Changchun 130012, China
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Received: 10 August 2017 / Revised: 17 September 2017 / Accepted: 21 September 2017 / Published: 28 September 2017
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Abstract

With the rapid development of sensor networks, big marine data arises. To efficiently use these data to predict thermoclines, we propose a machine learning approach. We firstly focus on analyzing how temperature, salinity, and geographic location features affect the formation of thermocline. Then, an improved model based on entropy value method for the thermocline selection is demonstrated. The experiments adopt BOA Argo data sets and the experimental results show that our novel model can predict thermoclines and related data effectively. View Full-Text
Keywords: thermocline; machine learning; statistical learning; entropy value calculation thermocline; machine learning; statistical learning; entropy value calculation
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Jiang, Y.; Gou, Y.; Zhang, T.; Wang, K.; Hu, C. A Machine Learning Approach to Argo Data Analysis in a Thermocline. Sensors 2017, 17, 2225.

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