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Modeling method for soil heavy mental content based on forward interval partial least squares algorithm

A technology of partial least squares and modeling methods, which is applied in the direction of measuring devices, complex mathematical operations, instruments, etc., can solve the problems of spectral noise interference and the inability to better exclude heavy metal irrelevant spectral components, and achieve simple modeling process and model Easy to improve the effect of model accuracy

Inactive Publication Date: 2018-02-23
CHINA THREE GORGES UNIV
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Problems solved by technology

At present, the heavy metal correlation model cannot well exclude the spectral components irrelevant to the heavy metal to be measured, and is easily interfered by spectral noise.

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  • Modeling method for soil heavy mental content based on forward interval partial least squares algorithm
  • Modeling method for soil heavy mental content based on forward interval partial least squares algorithm
  • Modeling method for soil heavy mental content based on forward interval partial least squares algorithm

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Embodiment Construction

[0019] A method for modeling soil heavy metal content based on forward interval partial least squares algorithm, comprising the following steps:

[0020] Step 1: The discrete spectrum output by the X-ray fluorescence spectrometer is divided into k bands of substantially equal width w i . denoted as candidate set W step ={w i |1≤i≤k}, step=0. where each band w i Contains C / k channels, where C is the number of channels contained in a complete spectrum. Also specify the selected set (empty set), step=0. After the original spectral signal of a sample is collected by the spectrometer, it will be converted into a series of discrete digital signal values, that is, channels. For the acquisition of a spectrum, the number of spectral channels C output by the spectrometer can usually be configured to be 1024, 4096, or 8192, and each channel corresponds to the spectral intensity at a certain wavelength.

[0021] Step 2: Use the PLS (Partial Least Squares) algorithm to establish ...

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Abstract

The invention relates to a modeling method for soil heavy mental content based on a forward interval partial least squares algorithm. The method comprises the following steps: dividing the whole heavymetal fluorescence spectrum area into k wavebands in equal width; establishing a partial least squares model for each sub-band, thereby acquiring k local regression models; measuring the model precision on the basis of RMSECV value; taking the waveband corresponding to the local model in the highest precision as a first selected waveband and taking the local model as a first sub-model; jointing the other (k-1) wavebands with the first selected waveband in turn, thereby acquiring (k-1) local models; selecting the waveband corresponding to the local model with the lowest RMSECV value as a second selected waveband and taking the local model as a second sub-model; repeating the processes till jointing wall the wavebands; inspecting the RMSECV value of each sub-model and selecting the sub-model with the optimal performance from all the sub-models: taking the section combination corresponding to the minimal RMSECV as the optimal combination. According to the invention, the spectrum range used by the model is optimized and the precision of the soil heavy mental quantitative detection model is increased.

Description

technical field [0001] The invention relates to a soil heavy metal quantitative detection modeling method, in particular to a soil heavy metal content modeling method based on forward interval partial least squares algorithm. Background technique [0002] Soil heavy metal pollution is one of the most harmful and widespread environmental problems in soil pollution. Therefore, the detection of heavy metals in soil has become an important task in environmental protection and agricultural production, and it is also the primary link in the treatment and restoration of polluted soil. EDXRF (Energy X-ray Fluorescence) spectroscopy has the advantages of fast analysis speed, low cost, simple operation, high precision, and in-situ detection, and has been applied in many heavy metal analysis fields. However, the quantitative analysis of heavy metals in soil is still in the exploratory stage. Due to the complex composition of the soil sample and the relatively low content of heavy met...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N23/223G06F17/16
Inventor 肖敏胡骞梁静
Owner CHINA THREE GORGES UNIV
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