Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap
Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap
Autori:
Izdanje: Sinteza 2023 - International Scientific Conference on Information Technology and Data Related Research
DOI: 10.15308/Sinteza-2023-17-22
Oblast: Computer Science and Artificial Intelligence
Stranice: 17-22
Apstrakt:
This study used an improved version of the reptilian search algorithm to investigate atmospheric patterns of toluene and its interactions with other polluting species under different environmental conditions. Toluene is a harmful aromatic hydrocarbon known for its role in the formation of secondary atmospheric pollutants. In this study, a two-year database of hourly pollutant concentrations, such as toluene, was analysed. The results were validated against other models using metaheuristic algorithms, and Shapley's additive explanations method was used to interpret them. The findings indicated a distinct correlation between toluene and m,p-xylene, and the study described the environmental conditions that influence their interactions. Overall, this research highlights the significance of using advanced analytical techniques to better understand the relationships between pollutants and their behaviour in different environmental conditions.
Ključne reči: Machine Learning, Extreme Gradient Boosting, Metaheuristics, Explainable Artificial Intelligence, Volatile Organic Compounds
Priložene datoteke:
- US - SINTEZA - 2023 - RAD 3 - 17-22 ( veličina: 366,83 KB, broj pregleda: 166 )
Kategorije objave:
Radovi na konferenciji Sinteza 2023, Beograd, Srbija
Zahvaljujemo se što ste preuzeli publikaciju sa portala Singipedia.
Ukoliko želite da se prijavite za obaveštenja o sadržajima iz oblasti ove publikacije, možete nam ostaviti adresu svoje elektronske pošte.
Preuzimanje citata:
BibTeX format
RefWorks Tagged format
Unapred formatirani prikaz citata
BibTeX format
@article{article, author = {G. Jovanović, M. Perišić, S. Stanišić, N. Bačanin Džakula and A. Stojić}, title = {Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap}, journal = {Sinteza 2023 - International Scientific Conference on Information Technology and Data Related Research}, year = 2023, pages = {17-22}, doi = {10.15308/Sinteza-2023-17-22} }
RT Conference Proceedings A1 Gordana Jovanović A1 Mirjana Perišić A1 Svetlana Stanišić A1 Nebojša Bačanin Džakula A1 Andreja Stojić T1 Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap AD Univerzitet Singidunum, Beograd, Beograd, Srbija YR 2023 NO doi: 10.15308/Sinteza-2023-17-22
G. Jovanović, M. Perišić, S. Stanišić, N. Bačanin Džakula and A. Stojić, Revealing Toluene Behaviour in the Atmosphere Based on Coupling of Metaheuristics, Xgboost, and Shap, Univerzitet Singidunum, Beograd, 2023, doi:10.15308/Sinteza-2023-17-22