Optimizing a hybrid process of electrolysis ultrasound and persulfate for remediation of petroleum contaminated soils using AI models

Abstract Research uses both RANSAC Regressor and Monte Carlo Optimization to improve the performance of electrolysis/ultrasound/persulfate system which detoxifies petroleum-contaminated soils. The Artificial Intelligence (AI) models used to optimize six process parameters showed X2 (humidity) and X3...

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Autors principals:	Rozhan Feizi, Iman Parseh, Ali Zafarzadeh, Sahand Jorfi, Amir Sheikhmohammadi
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2025-07-01
Col·lecció:	Scientific Reports
Matèries:	Hybrid electrolysis AI models RANSAC regressor Monte Carlo optimization Soil remediation Electrolysis-Ultrasound hybrid
Accés en línia:	https://doi.org/10.1038/s41598-025-06819-8
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