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...

This study aims to investigate the traffic information forecasting based on the data mining technology. As well known, useful knowledge in traffic management system often hides in a large amount of traffic data. Generally, prior data pattern labels have been used to train the Artificial Neural Network (ANN) to identify the traffic conditions in the traffic information forecasting. The performan...

the purpose of this study is to investigate the accuracy of predictions of aniline removal efficiency in a moving bed biofilm reactor (mbbr) by various methods, namely by rbf, anfis, and fuzzy regression analysis. the reactor was operated in an aerobic batch and was filled by light expanded clay aggregate (leca) as a carrier for the treatment of aniline synthetic wastewater. exploratory data an...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

: The Artificial Neural Network (ANN) is an Intelligence technique that offer many benefits including the ability to process a vast amount of data, learn from experiences, and good generalization capability. It was invented based on concept imitation human brain built up nodes are like neurons. Radial Basis Function (RBF) one established types ANN. Considering advantages great performance RBF, ...

A new model of pattern recognition principles—Biomimetic Pattern Recognition, which is based on “matter cognition” instead of “matter classification”, has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuro...

ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression...

Truncated sharp crested weirs are used to measure flow rate and control upstream water surface in irrigation canals and laboratory flumes. The main advantages of such weirs are ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for estimation of hydraulic data. In...