Prof. E. R. AdagunodoBALOGUN, Oluwatobi2026-08-282026-08-282016-07-28https://ir.bellsuniversity.edu.ng/handle/123456789/554xii,84pages,illustration.;hardbackThe advancement of the information and communication technology has created an unlimited space for exploration in different areas in order to make meaningful observations and predict at an optimum accuracy. All around the world, data are being generated every moment in large quantities, but these data are of no use until they can be converted to useful in formation. The limitation of existing models used for predicting River sediment yield in order to forestall against natural and economic disasters forms the basis of the motivation of this research. By taking advantage of the opportunities presented by the advancement of technology, this research focuses on predicting the sediment yield from Oyan gauging station of Ogun-Osun River Basin and comparing the output with result with other existing result. Some conventional method available for sediment load/yield estimation are largely empirical. In this research, an ANFIS (Adaptive Neuro-Fuzzy inference system) is used to predict the sediment yield of Oyan gauging station of Ogun-Osun River Basin. The ANFIS is a feed forward five layered architecture and uses the back propagation algorithm to train the network. For this research, four inputs data are used, the water stage and water stage and water discharge, water temperature, and rainfall.enAttribution 4.0 InternationalTechnologyInformationDissertation