Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS
Ba-based ion interference with Eu in coal and coal combustion products during quadrupole-based inductively coupled plasma mass spectrometry procedures is problematic. Thus, this paper proposes machine-learning-based prediction models for determination of the threshold value of Ba interference with E...
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doaj-63239c8db2bd42129cad45d4477263112020-11-25T02:11:58ZengMDPI AGMinerals2075-163X2019-04-019525910.3390/min9050259min9050259Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MSNa Xu0Qing Li1College of Geoscience and Survey Engineering, China University of Mining and Technology, Beijing 100083, ChinaDepartment of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, HKSAR, Hong Kong, ChinaBa-based ion interference with Eu in coal and coal combustion products during quadrupole-based inductively coupled plasma mass spectrometry procedures is problematic. Thus, this paper proposes machine-learning-based prediction models for determination of the threshold value of Ba interference with Eu, which can be used to predict such interference in coal. The models are trained for Eu, Ba, Ba/Eu, and Ba interference with Eu. Under different user-defined parameters, different prediction models based on the corresponding model tree can be applied to Ba interference with Eu. We experimentally show the effectiveness of these different prediction models and find that, when the Ba/Eu value is less than 2950, the Ba-Eu interference prediction model is <inline-formula> <math display="inline"> <semantics> <mrow> <mi>y</mi> <mo>=</mo> <mo>−</mo> <mn>0.18419411</mn> <mo>+</mo> <mn>0.00050737</mn> <mo>×</mo> <mi>x</mi> <mo>,</mo> <mtext> </mtext> <mn>0</mn> <mo><</mo> <mi>x</mi> <mo><</mo> <mn>2950</mn> <mo>.</mo> </mrow> </semantics> </math> </inline-formula> Further, when the Ba/Eu value is between 2950 and 189,523, the Ba-Eu interference prediction model of <inline-formula> <math display="inline"> <semantics> <mrow> <mi>y</mi> <mtext> </mtext> <mo>=</mo> <mtext> </mtext> <mn>0.293982186</mn> <mtext> </mtext> <mo>+</mo> <mtext> </mtext> <mn>0.00000181729975</mn> <mtext> </mtext> <mo>×</mo> <mtext> </mtext> <mi>x</mi> <mo>,</mo> <mtext> </mtext> <mn>2950</mn> <mtext> </mtext> <mo><</mo> <mtext> </mtext> <mi>x</mi> <mtext> </mtext> <mo><</mo> <mtext> </mtext> <mn>189</mn> <mo>,</mo> <mn>523</mn> </mrow> </semantics> </math> </inline-formula> yields the best result. Based on the optimal model, a threshold value of 363 is proposed; i.e., when the Ba/Eu value is less than 363, Ba interference with Eu can be neglected during Eu data interpretation. Comparison of this threshold value with a value proposed in earlier works reveals that the proposed prediction model better determines the threshold value for Ba interference with Eu.https://www.mdpi.com/2075-163X/9/5/259europiumICP-Q-MSpolyatomic ion inferencecoalmachine learningregression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Na Xu Qing Li |
spellingShingle |
Na Xu Qing Li Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS Minerals europium ICP-Q-MS polyatomic ion inference coal machine learning regression |
author_facet |
Na Xu Qing Li |
author_sort |
Na Xu |
title |
Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS |
title_short |
Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS |
title_full |
Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS |
title_fullStr |
Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS |
title_full_unstemmed |
Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS |
title_sort |
threshold value determination using machine learning algorithms for ba interference with eu in coal and coal combustion products by icp-ms |
publisher |
MDPI AG |
series |
Minerals |
issn |
2075-163X |
publishDate |
2019-04-01 |
description |
Ba-based ion interference with Eu in coal and coal combustion products during quadrupole-based inductively coupled plasma mass spectrometry procedures is problematic. Thus, this paper proposes machine-learning-based prediction models for determination of the threshold value of Ba interference with Eu, which can be used to predict such interference in coal. The models are trained for Eu, Ba, Ba/Eu, and Ba interference with Eu. Under different user-defined parameters, different prediction models based on the corresponding model tree can be applied to Ba interference with Eu. We experimentally show the effectiveness of these different prediction models and find that, when the Ba/Eu value is less than 2950, the Ba-Eu interference prediction model is <inline-formula> <math display="inline"> <semantics> <mrow> <mi>y</mi> <mo>=</mo> <mo>−</mo> <mn>0.18419411</mn> <mo>+</mo> <mn>0.00050737</mn> <mo>×</mo> <mi>x</mi> <mo>,</mo> <mtext> </mtext> <mn>0</mn> <mo><</mo> <mi>x</mi> <mo><</mo> <mn>2950</mn> <mo>.</mo> </mrow> </semantics> </math> </inline-formula> Further, when the Ba/Eu value is between 2950 and 189,523, the Ba-Eu interference prediction model of <inline-formula> <math display="inline"> <semantics> <mrow> <mi>y</mi> <mtext> </mtext> <mo>=</mo> <mtext> </mtext> <mn>0.293982186</mn> <mtext> </mtext> <mo>+</mo> <mtext> </mtext> <mn>0.00000181729975</mn> <mtext> </mtext> <mo>×</mo> <mtext> </mtext> <mi>x</mi> <mo>,</mo> <mtext> </mtext> <mn>2950</mn> <mtext> </mtext> <mo><</mo> <mtext> </mtext> <mi>x</mi> <mtext> </mtext> <mo><</mo> <mtext> </mtext> <mn>189</mn> <mo>,</mo> <mn>523</mn> </mrow> </semantics> </math> </inline-formula> yields the best result. Based on the optimal model, a threshold value of 363 is proposed; i.e., when the Ba/Eu value is less than 363, Ba interference with Eu can be neglected during Eu data interpretation. Comparison of this threshold value with a value proposed in earlier works reveals that the proposed prediction model better determines the threshold value for Ba interference with Eu. |
topic |
europium ICP-Q-MS polyatomic ion inference coal machine learning regression |
url |
https://www.mdpi.com/2075-163X/9/5/259 |
work_keys_str_mv |
AT naxu thresholdvaluedeterminationusingmachinelearningalgorithmsforbainterferencewitheuincoalandcoalcombustionproductsbyicpms AT qingli thresholdvaluedeterminationusingmachinelearningalgorithmsforbainterferencewitheuincoalandcoalcombustionproductsbyicpms |
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