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 presents a methodology to formulate natural language rules for an adaptive neuro-fuzzy system based on discovered knowledge, supported by prior knowledge and statistical modeling. These rules could be improved using statistical methods and neural nets. This gives clinicians a valuable tool to explore the importance of different variables and their relations in a disease and could aid...

A new methodology for simulating the flow field inside an arteriovenous (AV) graft to vein anastomoses by the adaptive neuro fuzzy inference system (ANFIS) is presented in this study. For determining the optimal AV graft angle, an ANFIS-based model of neuro fuzzy-graft-vein (NF-GVEIN) is proposed. Therefore engineering design of the graft can be supported. The advantage of this neuro-fuzzy hybr...

In this study two techniques, for modeling electricity consumption of the Jordanian industrial sector, are presented: (i) multivariate linear regression and (ii) neuro-fuzzy models. Electricity consumption is modeled as function of different variables such as number of establishments, number of employees, electricity tariff, prevailing fuel prices, production outputs, capacity utilizations, and...

This paper addresses the issue of controlling nonlinear processes by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a neuro-fuzzy process model is suggested as a means to model processes with strong nonlinearities depending on the operating region. In this paper the neurofuzzy approach is used for the modelling and control of a strongly nonlinear pH...

This study presents a novel controller of magnetic levitation system by using new neuro-fuzzy structures which called flexible neuro-fuzzy systems. In this type of controller we use sliding mode control with neuro-fuzzy to eliminate the Jacobian of plant. At first, we control magnetic levitation system with Mamdanitype neuro-fuzzy systems and logical-type neuro-fuzzy systems separately and then...

The design of a support vector machine with Gaussian kernels is considered for modeling nonlinear processes. The structure is equivalent to a neuro-fuzzy system based on radial basis function network considering some restrictions. To improve the interpretability and reduce the complexity of the structure a hybrid learning scheme is proposed. First, the input-output data is supervised clustered ...

Weather prediction is an ever challenging area of investigation for scientists. The Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different ki...