http://popups.lib.uliege.be/1373-5411/index.php?id=2471 Publications of Auteurs Ebrahim Jabbari fr 0 http://popups.lib.uliege.be/1373-5411/index.php?id=2649 The methods of ordinary least-squares regression (OLSR), fuzzy regression (FR), and adaptive network fuzzy inference system (ANFIS) are compared in inferring operating rules for a reservoir operations problem. Dynamic programming (DP) is used as an optimization tool to provide the input-output data set to be used by OLSR, FR, and ANFIS models. The OLSR. FR. and ANFIS based rules are then simulated and compared. The methods are applied to a long-term planning problem as well as to a medium-term implicit stochastic optimization model. The results indicate that FR is useful to derive operating rules for a long-term planning model, where imperfect and partial information is available. ANFIS is beneficial in medium term optimization as it is able to extract important features of the system from the generated input-output set. Thu, 29 Aug 2024 16:07:06 +0200 Thu, 10 Oct 2024 16:25:39 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=2649 http://popups.lib.uliege.be/1373-5411/index.php?id=2469 Two important characteristics of the hydrologic phenomena are their non-linear behaviour and uncertainty and ambiguity in their nature. So, as a hydrologic phenomenon, the sediment transport possesses a kind of uncertainty and ambiguity as well. Recently, use of Artificial Neural Networks (ANNs) and fuzzy sets in simulation and modelling of the systems with uncertainty bas produced suitable results. In this research, for modelling and prediction of sediment transport of river flows, the Adaptive Neuro-Fuzzy Inference System (ANFIS) as a method based on the ANNs and fuzzy sets was used. Using several ANNs and ANFIS models for prediction of sediment load transport showed that using the river discharge in the current period and the river discharge and the sediment load in the previous period as the models nodes, yields the best results. Thu, 22 Aug 2024 15:00:19 +0200 Thu, 22 Aug 2024 15:00:28 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=2469