Heavy metal content support vector machine regression method combining bands and ratio combinations of indoor and outdoor spectrums

A technology of support vector machine and regression method, which is applied in the field of heavy metal content support vector machine regression, can solve the problems of difficult indoor spectrum, poor identification of ground objects, affecting the inversion effect of heavy metals, etc., so as to improve the inversion accuracy and eliminate the Effects of Soil Spectral Differences

Pending Publication Date: 2020-08-25
HUNAN CITY UNIV
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Although the above-mentioned hyperspectral inversion modeling of heavy metal content in soil has the advantages of less cost and higher efficiency, due to the differences in soil spectra caused by different environmental conditions such as indoor and outdoor atmospheres, it is difficult to directly apply indoor spectra to field large-scale models. Scope soil heavy metal pollution investigation; single-band is likely to cause poor identifiability of ground features, and soil background information is not easy to separate, which affects the effect of heavy metal inversion; the soil composition is complex, and the linear regression effect of heavy metal content is not ideal

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Heavy metal content support vector machine regression method combining bands and ratio combinations of indoor and outdoor spectrums
  • Heavy metal content support vector machine regression method combining bands and ratio combinations of indoor and outdoor spectrums
  • Heavy metal content support vector machine regression method combining bands and ratio combinations of indoor and outdoor spectrums

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

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

[0043] Such as Figure 1-Figure 3 Shown, the heavy metal content support vector machine regression method of the band and the ratio combination of the combined indoor and outdoor spectrum of the present invention, its steps are:

[0044] Step S1: soil sample collection and soil spectrum measurement;

[0045] Step S2: KS-DS algorithm constructs the spectral conversion model; that is, constructs the indoor and outdoor spectral conversion models of the selected conversion set samples;

[0046] Step S3: Spectral preprocessing and correlation analysis; that is, use the constructed soil indoor and outdoor spectral conversion model to perform spectral conversion on the outdoor spectrum of the soil sample to obtain the converted outdoor soil spectral data; construct a strong correlation band and band ratio combination model, the band The Pe...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a heavy metal content support vector machine regression method combining bands and ratio combinations of indoor and outdoor spectrums. The method comprises the following steps:S1, collecting a soil sample and measuring a soil spectrum; S2, constructing a spectrum conversion model by using a KS-DS algorithm; S3, carrying out spectrum pretreatment and correlation analysis; and S4, constructing a support vector machine heavy metal content inversion model fusing indoor and outdoor spectrums, and carrying out detection. The method has the advantages of simple principle, high inversion precision, good detection effect and the like.

Description

technical field [0001] The invention mainly relates to the technical field of soil heavy metal detection, in particular to a heavy metal content support vector machine regression method combining indoor and outdoor spectrum bands and ratio combinations. Background technique [0002] A large amount of heavy metals in the soil can contaminate crops, endanger human health through the food chain, and cause cancer risk. Accurate and efficient determination of soil heavy metal content and effective implementation of comprehensive prevention and control of heavy metal-contaminated soil are gradually becoming a hot spot of global concern. At present, the investigation of soil heavy metal content mostly relies on field sampling and laboratory chemical analysis by atomic absorption spectrophotometry. Although this method has high precision and high reliability, it is costly and time-consuming. [0003] Hyperspectral technology has been widely used in quantitative inversion research ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01N21/25G06K9/62G06F17/18
CPCG01N21/25G06F17/18G06F18/2411
Inventor 薛云邹滨涂宇龙
Owner HUNAN CITY UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap