A Recurrent Trainable Neural Network (RTNN) with a two layer canonical architecture and a dynamic Backpropagation leamng method are applied for identification and control of complex nonlinear mechanical plants. The paper uses a Fuzzy-Neural Hierarchical Multi-Model (FNHMM), which merge the fuzzy model flexibility with the learning abilities of the RNNs. The paper proposed the application of two...

The Call admission control (CAC) is one of the Radio Resource Management (RRM) techniques that plays influential role in ensuring the desired Quality of Service (QoS) to the users and applications in next generation networks. This paper proposes a fuzzy neural approach for making the call admission control decision in multi class traffic based Next Generation Wireless Networks (NGWN). The propo...

This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural ...

We present a comparative study of electricity consumption predictions using the SARIMAX method (Seasonal Auto Regressive Moving Average eXogenous variables), HyFis2 model (Hybrid Neural Fuzzy Inference System) and LSTNetA (Long Short Time series Network Adapted), hybrid neural network containing GRU (Gated Recurrent Unit), CNN (Convolutional Network) dense layers, specially adapted for this cas...

In this paper we solve a wide rang of Semidefinite Programming (SDP) Problem by using Recurrent Neural Networks (RNNs). SDP is an important numerical tool for analysis and synthesis in systems and control theory. First we reformulate the problem to a linear programming problem, second we reformulate it to a first order system of ordinary differential equations. Then a recurrent neural network...

this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. this paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. for this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. the sugg...

Energy accounting is a system for regularly measuring, analyzing, and reporting the energy use of various activities. This done to increase efficiency monitor impact usage on environment. Primary now by determining amount fossil fuel required generate it. However, if fuels become scarcer, this strategy becomes less viable. Instead, new approach will be required, one that takes into consideratio...