Abstract There is a growing interest in automatic crafting of neural network architectures as opposed to expert tuning find the best architecture. On other hand, problem stock trading considered one most dynamic systems that heavily depends on complex trends individual company. This paper proposes novel self-evolving system called Multi-Layer Perceptron (seMLP) which can abstract data and produ...

Is there any potential benefit when training threshold circuits by adding extra layers (depth) to the network? This question is investigated in a powerful recently introduced artificial intelligence system, called the Logarithmic Simulated Annealing (LSA) machine, that combines the Simulated Annealing Algorithm with a Logarithmic cooling schedule and the classical perceptron algorithm. The firs...

Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image arti...

It is accepted that the activity of the vehicle pedals (i.e., throttle, brake, clutch) reflects the driver's behavior, which is at least partially related to the fuel consumption and vehicle pollutant emissions. This paper presents a solution to estimate the driver activity regardless of the type, model, and year of fabrication of the vehicle. The solution is based on an alternative sensor syst...

This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the original time series into a set of N −dimensional vectors, an Information-Theoretic based clustering method that segments the previous set into subspaces of similar vectors and a set of single layer neural networks tha...

An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...

Using measurements of Sea Surface Salinity and Sea Surface Temperature in the Western Tropical Atlantic Ocean, from 2003 to 2007 and 2009, we compare two approaches for estimating Sea Surface Salinity : Multiple Non-linear Regression and Multi Layer Perceptron. In the first experiment, we use 18,300 in situ data points to establish the two models, and 503 points for testing their extrapolation....

The view of artificial neural networks as adaptive systems has lead to the development of ad-hoc generic procedures known as learning rules. The first of these is the Perceptron Rule (Rosenblatt, 1962), useful for single layer feed-forward networks and linearly separable problems. Its simplicity and beauty, and the existence of a convergence theorem made it a basic departure point in neural lea...