Taher Abunama

TL;DR: Gene expression programming (GEP) outperformed both artificial neural network (ANN) and linear and non-linear regression models for TDS and EC and sensitivity and parametric analyses revealed that bicarbonate is the most sensitive parameter influencing both T DS and EC models.

TL;DR: The outcomes of this study recommend an integrated scenario of anaerobic digestion and recycling techniques to be employed in Malaysia and show that the first scenario generates huge amount of leachate and hazardous air constituents.

TL;DR: Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models were able to provide a good performance in the modeling of leachate generation efficiently.

TL;DR: Based on the available literature, it can be deduced that the complete adoption of EC management practices from developed countries might only contribute partly in the mitigation of EC pollution in South Africa and an EC monitoring programme specific to the country is recommended which should be based on their occurrence levels, sources and removal in WWTPs.

TL;DR: The final evaluation of NAR and SVM demonstrated that SVM made better predictions at peak flow and NAR fit well for low and average inflow ranges.