Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions

• Main Authors: Ehteram, M., Ghotbi, S., Kisi, O., Ahmed, A.N., Hayder, G., Fai, C.M., Krishnan, M., Afan, H.A., EL-Shafie, A.
• Format: Article
• Language: English
• Published: 2020
• Institution: Universiti Tenaga Nasional

Suspended sediment load (SLL) prediction is a significant field in hydrology and hydraulic sciences, as sedimentation processes change the soil quality. Although the adaptive neuro fuzzy system (ANFIS) and multilayer feed-forward neural network (MFNN) have been widely used to simulate hydrological v...