Semi-supervised fuzzy recognition model and soil humidity measurement method based on model
A fuzzy recognition, soil moisture technology, applied in the direction of measuring devices, using microwaves to test moisture content, instruments, etc., can solve the problem of low accuracy
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Embodiment 1
[0090] The semi-supervised fuzzy recognition model of the present invention has a process as follows: figure 1 shown, including the following steps:
[0091] Step 1: Data Acquisition
[0092] like figure 2 As shown in the figure, a surveying and mapping-level receiver is selected to be installed in the experimental site, output data in RINEX format, and obtain the required information from the O file and N file of the observation data; process the above O file and N file, and extract GPS and GLONASS satellites from them. Elevation, azimuth, UTC time and SNR data of different satellites. The extracted data is screened, and a low elevation angle is selected, and in the present embodiment, the data whose azimuth angle remains basically unchanged in the range of 2°-25° is selected;
[0093] Step 2: Data Preprocessing
[0094] In the original SNR data, there are many noises, which are caused by complex factors such as hardware, weather, and temperature. Some data need to be r...
Embodiment 2
[0165] On the basis of Embodiment 1, the method for measuring soil moisture based on a semi-supervised fuzzy recognition model of the present invention includes the following steps:
[0166] Step 21: establish a semi-supervised fuzzy recognition model;
[0167] Step 22: Model prediction, bring the test data into the above model to test the model accuracy, predict soil moisture, and perform soil moisture inversion.
[0168] The working principle of this embodiment is: take the GPS and GLONASS frequency (f), amplitude (A) and phase (P) observations obtained in step 4 as the eigenvalue x of the sample in the model ij , take one of the GPS and GLONASS samples as an example, record the GPS frequency observation as x 11 , the GLONASS frequency observations are x 12 , the GPS phase observation is x 13 , the GLONASS phase observation is x 14 , the GPS amplitude observation is x 15 , the GLONASS amplitude observation is x 16 , so n sample eigenvalue matrices The soil moisture s...
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