Sea water temperature and salinity information time sequence prediction method based on shipborne CTD measurement data

Abstract

The invention relates to a sea water temperature and salinity information time sequence prediction method based on shipborne CTD measurement data. The method comprises the following steps: collectingsea water temperature and conductivity data, and calculating salinity measurement data based on the measured conductivity information so as to obtain original temperature and salinity data; preprocessing original temperature and salinity data collected by a shipborne CTD, wherein the preprocessing process comprises interpolation, filtering and screening so as to obtain time sequence information conforming to a calculation standard; dividing the preprocessed data into time information and attribute information including temperature and salinity, and performing fuzzy rule division on the time information; acquiring a new membership function after threshold segmentation, performing sequence alignment on attribute information and time information after fuzzy segmentation to establish a new time sequence data set, and constructing the new membership data set by using the part of sequence information as a new fuzzy sequence number; designing a long-term and short-term memory neural network prediction model, setting a loss function, and training and establishing the prediction model by using the training set.

Description

technical field [0001] The invention belongs to the field of data processing, and relates to a method for processing data collected by a CTD (conductivity, temperature, and depth) instrument for marine data detection. Background technique [0002] With people's exploration of the ocean, the new generation of marine environment detection equipment has the advantages of high observation accuracy and wide measurement range, but it also increases the measurement volume of ocean data. Faced with the exponential growth of ocean big data processing problem, this study proposes a time series forecasting method based on fuzzy segmentation. At present, marine survey ships measure the temperature and salinity data of the mission sea area by deploying and launching CTD on board. However, the survey ship needs to repeatedly measure a sea area by means of wiring cruise. The measurement efficiency is low, and many wrong data will be collected, which will bring difficulties to the later da...

AI Technical Summary

Problems solved by technology

[0005] The present invention proposes a time series prediction method of seawater temperature and salinity information based on ship-borne CTD measurement data to solve the problem of time-series prediction of irregular environmental data collected by ship-borne CTD

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