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A research team from University of Anbar and Saudi universities obtained the acceptance of publication from a journal indexed within the journals of the first quartile
2025-04-24
A research team from the University of Anbar and Saudi universities obtained acceptance for publication from the journal :(Journal of Environmental Chemical Engineering (
Assistant lecturer Mohammed Majeed Humaid, a researcher at the Upper Euphrates Center for Sustainable Development Research at University of Anbar, and one of the members of the research team, said that this journal is indexed within the journals of the first quartile: )Q1 in Scopus and Clarivate - Cite score 11.4 - Impact factor 7.4 (.
Discussing the issue of heavy metals and their great threat to the ecosystem and human health, as they cause great damage through their effects on human health, water pollution, and soil degradation, monitoring these metals and estimating their concentrations accurately is crucial to avoid environmental problems caused by these dangerous metals as well as preparing deliberate plans to reduce their effects on the environment in the foreseeable future. Because the measurement, monitoring and prediction of their concentrations are complex processes, traditional methods generally do not achieve promising results and their accuracy and performance are relatively low and vary from case to case, so this study employed a large number of machine learning models where it found that the process Gaussian regression model (GPR) effectively predicts the bioavailability of heavy metals such as arsenic, cadmium, copper, chromium and zinc in composting environments, superior to other methods. The quantitative and visual evaluation also indicated that this model is very effective over a large number of artificial intelligence models used in this study, as well as other models, whether traditional or other, used in some previous studies.
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