A Machine Learning Approach to Argo Data Analysis in a Thermocline
AbstractWith 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
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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.
Jiang Y, Gou Y, Zhang T, Wang K, Hu C. A Machine Learning Approach to Argo Data Analysis in a Thermocline. Sensors. 2017; 17(10):2225.Chicago/Turabian Style
Jiang, Yu; Gou, Yu; Zhang, Tong; Wang, Kai; Hu, Chengquan. 2017. "A Machine Learning Approach to Argo Data Analysis in a Thermocline." Sensors 17, no. 10: 2225.
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