Neural Network Adaptive Modeling of Battery Discharge Behavior

Fuzzy, ANFIS and ICA Trained Neural Network Modeling of Ni-Cd Batteries Using Experimental Data

Nowadays, because of the many applications of batteries, modeling of this energy sources and accurate estimation of their behavior at different conditions is very important. In the traditional linear mathematical based models of batteries, nonlinear behavior of them and the variation of battery voltage during charge and discharge states are neglected. But various nonlinear physical, chemical an...

Modeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)

Evaluation of the Efficiency of the Adaptive Neuro Fuzzy Inference System (ANFIS) in the Modeling of the Ionosphere Total Electron Content Time Series Case Study: Tehran Permanent GPS Station

Global positioning system (GPS) measurements provide accurate and continuous 3-dimensional position, velocity and time data anywhere on or above the surface of the earth, anytime, and in all weather conditions. However, the predominant ranging error source for GPS signals is an ionospheric error. The ionosphere is the region of the atmosphere from about 60 km to more than 1500 km above the eart...

A Solution to the Problem of Extrapolation in Car Following Modeling Using an online fuzzy Neural Network

Car following process is time-varying in essence, due to the involvement of human actions. This paper develops an adaptive technique for car following modeling in a traffic flow. The proposed technique includes an online fuzzy neural network (OFNN) which is able to adapt its rule-consequent parameters to the time-varying processes. The proposed OFNN is first trained by an growing binary tree le...

Modeling of streamflow- suspended sediment load relationship by adaptive neuro-fuzzy and artificial neural network approaches (Case study: Dalaki River, Iran)

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 ...