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Near-sea-surface air temperature inversion method

A temperature and inversion technology, applied in neural learning methods, biological neural network models, design optimization/simulation, etc., can solve problems such as consuming a lot of manpower and material resources, improve efficiency, improve poor generalization, and optimize initial weights. The effect of the matrix

Active Publication Date: 2020-09-22
HARBIN ENG UNIV
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Problems solved by technology

[0004] Traditional sea-air data processing methods require a lot of manpower and material resources, and these methods are no longer applicable in today's ever-increasing data volume

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  • Near-sea-surface air temperature inversion method
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  • Near-sea-surface air temperature inversion method

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Embodiment Construction

[0042] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0043] The invention proposes a method for realizing the inversion of near-sea surface air temperature by establishing a training model based on a cyclic neural network. The specific implementation of this method includes determining the type of input and output parameters of the model, data preprocessing methods, weight initialization methods and the improvement of the structure of the cyclic neural network. The near-sea surface air temperature method described in the present invention uses the BPTT algorithm as the inversion method, and the execution flow is as follows figure 1 shown.

[0044] A kind of new near-sea surface air temperature inversion method that the present invention proposes, specifically comprises the following several steps:

[0045] Step 1: Select the sea area and extract and preprocess the data in the area.

[0046]...

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Abstract

The invention discloses a near-sea-surface air temperature inversion method. The method specifically comprises the steps: 1, selecting a sea area, and extracting and preprocessing data in the area; 2,determining input and output parameters, and establishing a near-sea-surface air temperature inversion model based on the recurrent neural network; 3, carring out weight initialization t; and 4, adding an L2 parameter paradigm penalty term; 5, initializing a BPTT algorithm; 6, performing forward propagation to obtain a predicted value; 7, updating the connection weight through back propagation; 8, calculating a loss function; and 9, returning and storing the metwork parameters. Compared with most near-sea-surface air temperature methods which only use linear regression and shallow neural network methods for modeling, the near-sea-surface air temperature inversion method has the advantages that the deep neural network is used for modeling and training, so that the near-sea-surface air temperature inversion precision is improved.

Description

technical field [0001] The invention relates to an inversion method of near-sea surface air temperature, belonging to the technical field of research on atmospheric and oceanic data processing methods. Background technique [0002] Near sea surface air temperature is a very important but difficult to obtain air-sea parameter. Since there is a certain correlation between the air-sea parameters, the relevant air-sea parameters can be used to obtain the near-sea surface air temperature by means of inversion. The inversion of near-sea surface air temperature is beneficial to the study of ocean-atmosphere interaction and also to people's understanding of climate change. At the same time, the acquisition of near-sea surface temperature by means of inversion can also provide support for various researches on the ocean and atmosphere, and contribute to the development of marine resource development, marine environmental protection and other fields. [0003] Big data is a hot topic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N3/04G06N3/08
CPCG06F30/27G06N3/084G06N3/045
Inventor 高峰周诗楠刘厂郭少彬
Owner HARBIN ENG UNIV
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