Active queue control aims to improve the overall communication network throughput, while providing lower delay and small packet loss rate. The basic idea is to actively trigger packet dropping (or marking provided by explicit congestion notification (ECN)) before buffer overflow. In this paper, two artificial neural networks (ANN)-based control schemes are proposed for adaptive queue control in...

We present a method of modifyiog the structure of radial basis function (RBF) network to work with nonstationary series that exhibit homogeneous nonstationary behavior. In the original RBF network, the hidden node’s function is to sense the trajectory of the time series and to respond when there is a strong correlation between the input pattern and the hidden node’s center. This type of respons...

An integrated modeling and robust model predictive control (MPC) approach is proposed for a class of nonlinear systems. First, the nonlinear system is identified off-line by a RBF-ARX model possessing linear ARX model structure and state-dependent Gaussian RBF neural network type coefficients. On the basis of the RBF-ARX model, a combination of a local linearization model and a polytopic uncert...

BACKGROUND The increase of intraabdominal pressure to 10 mmHg provokes a decrease of renal blood flow (RBF). Pneumoperitoneum during laparoscopic techniques with intra-abdominal pressure (IAP) to 15 mmHg, results in a decrease in RBF, urine output and glomerular filtration rate (GFR). PURPOSE Analyze the changes in RBF, urine output an GFR in a porcine experimental model during open vs laparo...

These experiments examined whether the conscious sinoaortic baroreceptor-denervated (SAD) rat, owing to its high spontaneous arterial pressure (AP) variability, might represent a model for renal blood flow (RBF) autoregulation studies. In eight SAD and six baroreceptor-intact rats, AP and RBF were recorded (1-h periods) before and after furosemide (10 mg/kg followed by 10 mg. kg(-1). h(-1) iv) ...

In this research, a radial basis function artificial neural network (RBF-ANN) model was developed to predict the hot deformation flow curves of API X65 pipeline steel. The results of the developed model were compared with the results of a new phenomenological model that has recently been developed based on a power function of Zener-Hollomon parameter and a third order polynomial function of str...

Speaker identification is the process of determining which registered speaker provides a given utterance. Speaker identification required to make a claim on the identity of speaker from the Ns trained speaker in its user database. In this study, we propose the combination of clustering algorithm and the classification technique – subtractive and Radial Basis Function (RBF). The proposed techniq...

This paper deals with the identification of nonlinear systems using multi-kernel approach. In this context, we have improved the Support Vector Regression (SVR) method in order to identify nonlinear complex system. Our idea consists in dividing the regressor vector in several blocks, and, for each one a kernel function is used. This blockwise SVR approach is called Support Kernel Regression (SK...

The identification of non-linear systems by artificial neural networks has been successfully applied in many applications. In this context, the radial basis function neural network (RBF-NN) is a powerful approach for non-linear system identification. An RBF neural network has an input layer, a hidden layer and an output layer. The neurons in the hidden layer contain Gaussian transfer functions ...

A neural network model based on a chaotic particle swarm optimization (CPSO) radial basis function-back propagation (RBF-BP) was suggested to improve the accuracy of reactor temperature prediction. The training efficiency RBF-BP is influenced some degree by large randomness initial weight and threshold. To address impact threshold uncertainty combined network, this paper proposes using algorith...