Co-remediation of refinery sludge oil with food waste digestate using machine learning model: A review

The disposal and management of refinery oil sludge pose significant environmental challenges and sustainable approaches for remediation. This article reviews the prospective strategy of co-remediating refinery, oil sludge with food waste digestate, using the optimization and predictive abilities of the Artificial Neural Network (ANN) models. By combining of refinery oil sludge and food waste digestate not only effectively resolves the problem of waste management but also presents positive prospects for the remediation of oil-contaminated soils. This review summarizes current research on the use of ANN models. Utilizing ANN models to co-remediate refinery oil sludge and food waste digestate offers a potential and long-term solution for researchers, environmental engineers, and policymakers seeking innovative solutions to the problems associated with waste management and soil remediation.