Accepted Manuscript Forecasting hydrological parameters for reservoir system utilizing artiﬁcial intelligent models and exploring their inﬂuence on operation performance Mohammed Falah Allawi, Othman Jaafar, Firdaus Mohamad Hamzah, Suhana Binti Koting, Nuruol Syuhadaa Binti Mohd, Ahmed El-Shaﬁe PII: S0950-7051(18)30499-4 DOI: https://doi.org/10.1016/j.knosys.2018.10.013 Reference: KNOSYS 4532 To appear in: Knowledge-Based Systems Received date : 16 May 2018 Revised date : 27 August 2018 Accepted date : 9 October 2018 Please cite this article as: M.F. Allawi, et al., Forecasting hydrological parameters for reservoir system utilizing artiﬁcial intelligent models and exploring their inﬂuence on operation performance, Knowledge-Based Systems (2018), https://doi.org/10.1016/j.knosys.2018.10.013 This is a PDF ﬁle of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its ﬁnal form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.