Abstract
Natural phenomena disturb marine ordinary states mainly by disturb the sea surface temperature. As temperature is the main factor that affects thermocline, in this paper we propose a method to quantitative analyze the correlation between El Niño and thermocline based on decision tree methods rather than qualitative analysis. The experiments use the refined BOA_Argo data and the decision trees are constructed with these data. We aim at making better use of thermocline and trying not to be harmed by natural disasters such as El Niño.
This work was supported in part from the National Natural Science Foundation of China (51409117, 51679105).
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Hu, C., Gou, Y., Zhang, T., Wang, K., He, L., Jiang, Y. (2018). Analysis of Thermocline Influencing Factors Based on Decision Tree Methods. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_54
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DOI: https://doi.org/10.1007/978-981-10-7605-3_54
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