Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

Albergaria, José Tomás; Martins, F.G.; Alvim-Ferraz, M.C.M.; Delerue–Matos, Cristina

doi:10.1007/s11270-014-2058-y

Cited by 12 publications

(3 citation statements)

References 24 publications

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“…In fact, multiple linear regression (MLR) can also be used for predicting a target parameter of samples in the situation where the number of wavelengths is less than the number of samples [ 31 ]. MLR is a classic linear algorithm and works to interpret linear relationship between one dependent variable and two or more independent variables [ 32 ]. In this study, based on the same selected optimal wavelengths, four MLR models including RC-NC-MLR, SR-NC-MLR, SPA-NC-MLR, and CARS-NC-MLR were respectively developed and assessed in terms of r and RMSE values.…”

Section: Resultsmentioning

confidence: 99%

Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

Zhang

Lin

et al. 2023

Molecules

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Citrus peels are rich in bioactive compounds such as vitamin C and extraction of vitamin C is a good strategy for citrus peel recycling. It is essential to evaluate the levels of vitamin C in citrus peels before reuse. In this study, a near-infrared (NIR)-based method was proposed to quantify the vitamin C content of citrus peels in a rapid way. The spectra of 249 citrus peels in the 912‒1667 nm range were acquired, preprocessed, and then related to measured vitamin C values using the linear partial least squares (PLS) algorithm, indicating that normalization correction (NC) was more suitable for spectral preprocessing and NC-PLS model built with full NC spectra (375 wavelengths) showed a better performance in predicting vitamin C. To accelerate the predictive process, wavelength selection was conducted, and 15 optimal wavelengths were finally selected from NC spectra using the stepwise regression (SR) method, to predict vitamin C using the multiple linear regression (MLR) algorithm. The results showed that SR-NC-MLR model had the best predictive ability with correlation coefficients (rP) of 0.949 and root mean square error (RMSEP) of 14.814 mg/100 mg in prediction set, comparable to the NC-PLS model in predicting vitamin C. External validation was implemented using 40 independent citrus peels samples to validate the suitability of the SR-NC-MLR model, obtaining a good correlation (R2 = 0.9558) between predicted and measured vitamin C contents. In conclusion, it was reasonable and feasible to achieve the rapid estimation of vitamin C in citrus peels using NIR spectra coupled with MLR algorithm.

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Section: Resultsmentioning

confidence: 99%

Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

Zhang

Lin

et al. 2023

Molecules

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“…Qin et al [7] found that higher flow rates did not significantly improve removal rates, and pulsed and continuous vapor extraction had almost the same contaminant removal effects in the sand column. Albergaria et al [8] used multiple linear regression and artificial neural network models to predict the remediation time and SVE efficiency. Wang et al [9] proposed that the vacuum degree of an SVE system is not linearly related to the extraction flow rate and that an optimal value exists.…”

Section: Introductionmentioning

confidence: 99%

Influence of extraction and injection conditions on the performance of thermal-enhanced soil vapor extraction

Yang,

Feng,

Zheng

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Thermal-enhanced soil vapor extraction (T-SVE) is an in-situ remedial technique that can address the limitations of contaminant mass transfer and soil permeability. The relative humidity of the injected air, heating temperature of the thermal well, extraction pressure, and extraction mode are important design parameters of a T-SVE system that determine the temporal and spatial distributions of soil temperature and removal rate. Using a thermal–hydraulic–chemical coupled model with the interphase mass transfer of contaminants and water evaporation/condensation, this study investigated the effects of relative humidity, heating temperature, extraction pressure, and extraction mode on T-SVE performance. The results showed that with an increase in relative humidity, the heating temperature of the contaminated soil significantly improved; however, the removal rate of contaminants decreased, particularly in the late stage of remediation. Considering the heating temperature of the thermal well, a critical air relative humidity value that significantly affects the removal rate of contaminants was observed. The heating temperature of the thermal well must be considered in engineering design; however, the evaluation of the relative humidity of the air cannot be ignored.

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“…Air pollution often experiences a high enough increase to have an impact on environmental pollution and human health [1]. Broadly speaking, the perceived health impacts are respiratory problems [2]. Related to this, the negative effects that will be felt in the future are damage to the lungs, heart, and other organs [3].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Method Air Quality Classification Analysis Model

Yanto¹,

Arlis²,

Na’am³

et al. 2022

TEM Journal

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This paper aims to present a discussion of air quality based on the classification analysis developed by hybrid method. Problems that occur, where the longer the air quality is getting worse and can cause serious problems for human life. The method in performing the used analysis consisted of K-Means clustering, Multiple Linear Regression (MRL), Artificial Neural Network (ANN), and Decision Tree Algorithm C.45. The results of MRL measurement show that correlation relationship is the same as the variable with an output of 70.7%. Then the results of determination with ANN showed an MSE value of 0.0018197 and output accuracy of 99.99%.

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Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

Cited by 12 publications

References 24 publications

Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

Influence of extraction and injection conditions on the performance of thermal-enhanced soil vapor extraction

Hybrid Method Air Quality Classification Analysis Model

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