In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...

We propose a general class of multilayer feed-forward neural networks where the combination of inputs in every node is formed by hybrid linear and nonlinear (of the morphological/rank type) operations. We demonstrate that this structure ooers eecient solutions to pattern classiication problems by requiring fewer nodes or fewer parameters to estimate than those needed by multilayer perceptrons. ...

−Keystroke Dynamics is behavioural biometric used to measure the typing rhythm of the user when an individual types on the keyboard. It is assumed as a robust behavioural biometric. The functionality of this biometric is to measure the dwell time and flight time for changing keyboard actions. The paper focuses on enhancement of security using individual’s typing actions to distinguish between a...

We propose a general class of multilayer feed-forward neural networks where the combination of inputs in every node is formed by hybrid linear and nonlinear (of the morphological/rank type) operations. For its design we formulate a methodology using ideas from the back-propagation algorithm and robust techniques to circumvent the non-diierentiability of rank functions. Experimental results in a...

ABSTRACT The contribution is aimed at predictive control of nonlinear processes with the help of artificial neural networks as the predictor. Since this methodology is relatively wide, paper only concentrates on the prediction via artificial neural networks. Special attention is paid to the usage of offline-learnt predictor based on multilayer feed forward neural network. The proposed method is...

We are discussing our experiments we made to learn feed-forward neural network for task of finding valid hyphenation points in all words of given language. Multilayer neural networks were succesfully used for solving of this difficult problem. The structure of the network used is given, together with a discussion about training sets, influence of input coding and results of experiments done for...

Aim of this contribution is to present the optimization of the laser cutting process by artificial neural networks. NeuroSolution for Excel 1.02 was used in order to interpret complicated dependencies between technological characteristics of laser cutting and output parameters. Multilayer feed forward neural networks are utilized for modelling and prediction of input parameters of laser cutting...

This paper discusses the use of artificial neural networks, trained with patterns extracted from trail data, as recommender systems. Feed-forward Multilayer-Perceptrons trained with the Backpropagation Algorithm were used to assign a rating to pairs of domains, based on the number of people that had traversed between them. The artificial neural network constructed in this project was capable of...

We devise a feed-forward Artiicial Neural Network (ANN) procedure for predicting utility loads and present the resulting predictions for two test problems given by \The Great Energy Predictor Shootout-The First Building Data Analysis and Prediction Competition" 1]. Key ingredients in our approach are a method (test) for determining relevant inputs and the Multilayer Perceptron. These methods ar...