in recent years, use of fuzzy collection theories for modeling of hydrological phenomenon's that is including complexity and uncertainly is considered scholars. so in this research, adaptive neuro-fuzzy inference system (anfis) is used for performance of river flow forecasting process. in this research, three parameters such as raining, temperature and daily discharge of lighvanchai basin ...

Water quality monitoring is crucial in managing water resources and ensuring their safety for human use environmental health. In the Al-Jawf Basin, we conducted a study on Quaternary aquifer, where various techniques were utilized to evaluate, simulate, predict groundwater (GWQ) irrigation. These include indices (IWQIs), geochemical modeling, multivariate statistical analysis, geographic inform...

One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines a methodology for consumer demand modeling and prediction in a real-time environment of an irrigation water distribution system. The approach is based on Adaptive Neuro-Fuzzy Inferences System (AN...

This paper proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting the surface roughness in turning operation for set of given cutting parameters, namely cutting speed, feed rate and depth of cut. Two different membership functions, triangular and bell shaped, were adopted during the training process of ANFIS in order to compare the prediction accuracy of surface roughness by t...

modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...

This study proposes a new Adaptive Neuro-Fuzzy Inference System (ANFIS) controller to control the power system tuned by wind turbine. The purpose of design is improve dynamical response systems after fault which voltage has been improved. effectiveness proposed approach studied under different situations three machines 9 bus turbine replaced equipped ANFIS controller. simulation results confirm...

The late detection of the kick (the entrance of underground fluids into oil wells) leads to oil well blowouts. It causes human life loss and imposes a great deal of expenses on the petroleum industry. This paper presents the application of adaptive neuro-fuzzy inference system designed for an earlier kick detection using measurable drilling parameters. In order to generate the initial fuzzy inf...

Sedimentation in reservoirs is an important issue that should be considered for the reservoirs operation and useful life. In this study, application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) in prediction of the sediment release from the bottom outlet using semi-cylinder for different variables was evaluated. Dimensionless parameters such as dimens...

This paper proposes the implementation of a very simple but efficient Adaptive Neuro-Fuzzy Inference System ( ANFIS )based algorithm to detect the edges of an gray scale image. The proposed approach begins by scanning the images using floating 3x3 pixel window. ANFIS system designed has 8 inputs, which corresponds to 8 pixels of instantaneous scanning matrix, one output that tells whether the p...