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2018 | OriginalPaper | Chapter

Thermocline Analysis Based on Entropy Value Methods

Authors : Chengquan Hu, Yu Gou, Tong Zhang, Kai Wang, Lili He, Yu Jiang

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

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Abstract

Temperature, salinity, and geographic locations are three important factors while determining thermocline. We mainly focus on analyzing how these factors affect the formation of thermocline using machine learning methods. An improvement based on ‘entropy value method’ while choosing thermocline is demonstrated in the paper. The experiments adopt Argo data sets and the experimental results show that machine learning methods can compute thermocline and related data effectively.

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previous chapter Analysis of Thermocline Influencing Factors Based on Decision Tree Methods
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Metadata
Title
Thermocline Analysis Based on Entropy Value Methods
Authors
Chengquan Hu
Yu Gou
Tong Zhang
Kai Wang
Lili He
Yu Jiang
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-7604-6

Electronic ISBN: 978-981-10-7605-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7605-3_55