Version 1
: Received: 15 January 2024 / Approved: 15 January 2024 / Online: 15 January 2024 (16:30:53 CET)
Version 2
: Received: 17 January 2024 / Approved: 17 January 2024 / Online: 17 January 2024 (09:25:24 CET)
How to cite:
Dong, D.; Ren, Y.; Zhang, M.; Feng, X.; Liu, K. Monitoring Method of VOCs Based on PID in Soil-water-gas Environment. Preprints2024, 2024011137. https://doi.org/10.20944/preprints202401.1137.v2
Dong, D.; Ren, Y.; Zhang, M.; Feng, X.; Liu, K. Monitoring Method of VOCs Based on PID in Soil-water-gas Environment. Preprints 2024, 2024011137. https://doi.org/10.20944/preprints202401.1137.v2
Dong, D.; Ren, Y.; Zhang, M.; Feng, X.; Liu, K. Monitoring Method of VOCs Based on PID in Soil-water-gas Environment. Preprints2024, 2024011137. https://doi.org/10.20944/preprints202401.1137.v2
APA Style
Dong, D., Ren, Y., Zhang, M., Feng, X., & Liu, K. (2024). Monitoring Method of VOCs Based on PID in Soil-water-gas Environment. Preprints. https://doi.org/10.20944/preprints202401.1137.v2
Chicago/Turabian Style
Dong, D., Xiujuan Feng and Kaiwei Liu. 2024 "Monitoring Method of VOCs Based on PID in Soil-water-gas Environment" Preprints. https://doi.org/10.20944/preprints202401.1137.v2
Abstract
In the moist environment of soil-water-air, there is a problem of low accuracy in monitoring Volatile Organic Compounds (VOCs) using a Photoionization Detector (PID). This paper analyzes the reasons for the low accuracy of the traditional Support Vector Machine (SVM) regression method. To address the issue, the PID signal is subjected to feature extraction and Principal Component Analysis (PCA) to reduce the data dimensionality. Moreover, the optimal SVM parameters are selected using a Genetic Algorithm (GA), and a combined approach of SVM regression with PCA and GA is utilized for PID signal regression analysis. And the effectiveness of the method is validated through extensive experiments and simulations. Furthermore, the influence of the sample quantity on the regression accuracy is analyzed, enabling accurate monitoring of VOCs concentration in a moist environment.
Keywords
Photoionization detector; VOCs; Principal Component Analysis; Genetic Algorithm
Subject
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Xiujuan Feng
Commenter's Conflict of Interests: Author