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Thermocline prediction method based on machine learning

A thermocline and prediction model technology, applied in the field of seawater detection, can solve the problems of less research on ocean thermocline prediction models, and achieve high accuracy

Pending Publication Date: 2020-06-09
TIANJIN UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although deep learning and big data theory have been widely used in other fields and achieved certain results, there are few studies on ocean thermocline prediction models

Method used

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  • Thermocline prediction method based on machine learning
  • Thermocline prediction method based on machine learning
  • Thermocline prediction method based on machine learning

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Embodiment Construction

[0014] The present invention proposes a thermocline prediction method based on machine learning, based on the data collected by Argo, and uses the PCA algorithm to preprocess the data, and the FCM algorithm based on the Laplacian kernel function to accurately classify the data set, and the BP neural network Construct the prediction model of the thermocline, its overall framework is as follows figure 1 shown. The specific evaluation method includes the following steps:

[0015] Step 1: For Argo data, the present invention uses a cubic spline interpolation method to perform interpolation preprocessing on the data. First divide the data into [a,b] intervals, n+1 nodes are divided into n intervals, and the cubic function of each interval is S i (X), according to the formula (1) to solve the matrix m i :

[0016]

[0017] where S″(x)=m i , h i =x i+1 -x i , i=1,2,…,n combined with m 1 =m 2 = 0, solve for m i , and integrate it twice to get S i (x), so as to obtain a ...

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Abstract

The invention relates to a thermocline prediction method based on machine learning, and the method comprises the steps: carrying out non-uniform correction of ocean sample data by employing cubic sample interpolation, carrying out dimension reduction of the data through a principal component analysis algorithm, dividing data levels through an FCM fuzzy clustering algorithm, and building a BP neural network training data set, thereby constructing a thermocline prediction model.

Description

technical field [0001] The invention belongs to the field of seacline detection and relates to a thermocline prediction method based on machine learning. Background technique [0002] Thyocline is an important physical phenomenon on the seabed. It is a water layer with significant changes in seawater parameters in the vertical direction, including thermocline, halocline, densocline, sound velocity, etc. Among them, because the temperature information in the ocean information is the most and the quality is the best, the research on the thermocline is more in-depth. At the same time, the study of the thermocline is of great significance in military affairs, and has a certain influence on the ups and downs of submarines. Therefore, whether it is the theoretical study of the thermocline or the establishment and prediction of the thermocline model, the thermocline is one of the core issues in the research and analysis of marine information at home and abroad. Previous studies ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G06N20/00
CPCG06N3/084G06N20/00G06N3/045G06F18/23213G06F18/23G06F18/24
Inventor 杨嘉琛吕彩云
Owner TIANJIN UNIV