Fast Quantitative Modelling Method for Infrared Spectrum Gas Logging Based on Adaptive Step Sliding Partial Least Squares

Li, Zhongbing; Pang, Wei; Liang, Haibo; Chen, Guihui; Duan, Hongming; Jiang, Chuandong

doi:10.3390/en15041325

Cited by 3 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Partial least square is a commonly used multivariate statistical method and mathematical optimization technique for building predictive models and solving multiple linear regression problems [25][26][27][28][29][30]. Compared with traditional multiple linear regression methods, PLS methods can effectively deal with high-dimensional data and multi-collinearity problems and also improve the predictive power of models.…”

Section: Modeling Methods and Model Evaluation 261 Pls-based Predicti...mentioning

confidence: 99%

Detection of Soluble Solids Content (SSC) in Pears Using Near-Infrared Spectroscopy Combined with LASSO–GWF–PLS Model

Zhan

et al. 2023

Agriculture

View full text Add to dashboard Cite

The soluble solids content (SSC) of pears is mainly composed of sugars, organic acids, and other soluble substances and is one of the important indices used to measure the sweetness and quality of pear juice. The SSC of pears is mainly composed of sugars, organic acids, amino acids, esters, alcohols, phenols, flavonoids, and other compounds, and different groups within these compounds have different characteristic absorption peaks corresponding to different characteristic wavelengths. Traditional methods such as genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) models used for screening characteristic wavelengths are mainly based on statistical methods, and characteristic wavelengths are selected by finding the wavelengths related to the changes in the concentration of the target analytes. By ignoring the molecular structure and chemical properties of the target analytes and disregarding the influence of the groups of the compounds in the target analytes on the spectral characteristics, wavelengths that are not related to the target analytes may be selected, thus affecting the accuracy of the analytical results. In this paper, a partial least squares (PLS) model was established based on the characteristic wavelengths of CARS, GA, and LASSO algorithms, and the best least absolute shrinkage and selection operator (LASSO) was selected and compared with the characteristic wavelengths selected by group weighted fusion (GWF). The LASSO regression was validated by 10-fold cross-validation to select the appropriate regularization parameter, and the 33 characteristic wavelengths correlated with the SSC of pears were selected in the full spectral range, and the 9 characteristic wavelengths corresponding to the group response were weighted and fused and input into the PLS regression model. Using an established model, the coefficient of determination (R2) and the root mean square error (RMSE) of the calibration set were 0.992 and 0.177%, respectively, and the R2 and RMSE of the test set were 0.998 and 0.128%, respectively. The R2 of our LASSO–GWF–PLS prediction model was improved from 0.975 to 0.998, indicating that the LASSO–GWF–PLS method has very good prediction ability for detection of SSC in pears.

show abstract

Section: Modeling Methods and Model Evaluation 261 Pls-based Predicti...mentioning

confidence: 99%

Detection of Soluble Solids Content (SSC) in Pears Using Near-Infrared Spectroscopy Combined with LASSO–GWF–PLS Model

Zhan

et al. 2023

Agriculture

View full text Add to dashboard Cite

show abstract

“…However, the performance of its infrared spectroscopy logging technology needs to be continuously improved, and the accuracy needs to be improved. Also, the harsh disturbance environment at the logging site will cause large errors in the use of logging tools [22]. Infrared spectrum analysis technology plays an important role but also has shortcomings, especially the complex band composition of the infrared spectrum.…”

Section: Introductionmentioning

confidence: 99%

A study on the measurement method of a two-component fluid proportion infrared spectrum based on HDC-PSAM

Liang¹,

Luo²,

Guo³

et al. 2022

Meas. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

When traditional infrared spectroscopy technology measures and analyzes the quantitative research of fluid, due to the complex band composition of infrared spectrum, weak absorption intensity and spectral signal, it is easy to be disturbed during measurement and increase the error, making the quantitative analysis of fluid inaccurate and difficult to achieve requirements for accurate analysis of fluids. In order to solve this problem, this paper uses the self-developed experimental apparatus, and takes water-based drilling fluid and diesel oil as the research objects, and proposes a new method for quantitative research of two-component proportional fluids based on HDC-PSAM. A large number of experiments are carried out on water-based drilling fluids, diesel and water mixtures, and a large number of spectral experimental data are preprocessed using moving window smoothing and normalization methods. Extracting effective features with Hybrid dilated convolution (HDC) and Pyramid self-attention modules (PSAM) , combined with Partial Least Squares Algorithm (PLS) to model fluid mixtures to achieve quantification of fluid mixtures calculate. The experimental results show that this method can reduce the influence of disturbance during measurement, has higher accuracy and stability, and effectively improves the measurement accuracy of infrared spectroscopy for quantitative analysis of fluids. At the same time, this method provides a strong technical support for the analysis of other fluids and the measurement of fluid mixture by using infrared spectroscopy technology.

show abstract

Multicomponent Alkane IR Measurement System Based on Dynamic Adaptive Moving Window PLS

Pang

Liang

et al. 2022

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

Fast Quantitative Modelling Method for Infrared Spectrum Gas Logging Based on Adaptive Step Sliding Partial Least Squares

Cited by 3 publications

References 35 publications

Detection of Soluble Solids Content (SSC) in Pears Using Near-Infrared Spectroscopy Combined with LASSO–GWF–PLS Model

Detection of Soluble Solids Content (SSC) in Pears Using Near-Infrared Spectroscopy Combined with LASSO–GWF–PLS Model

A study on the measurement method of a two-component fluid proportion infrared spectrum based on HDC-PSAM

Multicomponent Alkane IR Measurement System Based on Dynamic Adaptive Moving Window PLS

Contact Info

Product

Resources

About