Alternative forms of neural networks have been applied to forecast daily river flows on a continuous basis with the purpose of understanding how recent architectures like ANFIS, GRNN and RBF compare with traditional FFBP when monsoon-fed rivers involving significant statistical bias are involved. The forecasts are made at a location called Rajghat along river Narmada in India. Division of yearl...

evaporation, as a major component of the hydrologic cycle, plays a key role in water resources development and management in arid and semi-arid climatic regions. although there are empirical formulas available, their performances are not all satisfactory due to the complicated nature of the evaporation process and the data availability. this paper explores evaporation estimation methods based o...

prediction the river flow discharge values are important in the surface water resources management. find an appropriate model to accurately predictionof this parameter is one of the most important ways to simulation and prediction. in this study three anfis, svm and gp models were evaluated and compared to modeling the monthly flow discharge of nazloochi river in tapik hydrometric station that ...

This paper presents an adaptive neuro-fuzzy inference system (ANFIS), which has been adapted as an alternative to other classical models for estimating the vehicle delays at signalized junctions. Rules, fuzzification, and inference were modeled by ANFIS. In this model, a hybrid algorithm was used for training and tests. The artificial network used three input variables representing simulation o...

This paper discusses the application of support vector machine in the area of identification of nonlinear dynamical systems. The aim of this paper is to identify suitable model structure for nonlinear dynamic system. In this paper, Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Support Vector Regression (SVR) models are applied for identification of highly nonlinear dynamic process. The res...

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track rotational speed of a reference engine and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the system is developed and simulation results are presented. It is shown that the ANFIS controller is suitable for control systems with large time d...

Distribution of contact pressure between the bipolar plate and gas diffusion layer considerably affect the performance of proton exchange membrane fuel cell. In this regard, an adaptive neuro-fuzzy inference system (ANFIS) is developed to predict the contact pressure distribution on the gas diffusion layer due to dimensional errors of the bipolar plate ribs in a proton exchange membrane fuel ce...

Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited reserves and developing a useful abstraction management strategy. The purpose this study was to assess the predictive accuracy estimation capability various models based on Adaptive Neuro Fuzzy Inference System (ANFIS). These included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimizatio...

Electrical load forecasting is well-known as one of the most important challenges in the management of electrical supply and demand and has been studied extensively. Electrical load forecasting is conducted at different time scales from short-term, medium-term and long-term load forecasting. Adaptive neuro-fuzzy inference system is a model that combines fuzzy logic and adaptive neuro system and...

Most practices applied in the development of lighting usage profile do not reflect the complexity occupants have on lighting loads in residential buildings. This study involves the use of Adaptive Neural Fuzzy Inference System (ANFIS) and regression model for residential load usage profile development, prediction and evaluation for energy and demand side management initiatives. Three variables ...