Over the last ten years feed-forward neural networks have become a popular tool for statistical decision making. During this time, they have been applied in many fields, including cytological classification. Neural networks are often treated as a black box, whose inner workings are concealed from the researcher. This is unfortunate, since the inner workings of a neural network can be understood...

CNC machining is known as an advanced machining process increasingly used for modern materials. This paper outlines modeling methodology applied to optimize cutting parameters during CNC milling with ball end mill tool. The parameters taken into account were radial depth of cut and feed per tooth. A predictive model was based on artificial neural network approach. Key-Words: Modeling, artificia...

This paper presents an application of Neural Networks to the control of a real system with measurement noise. The details of the system and the implementation of sensor, controller and actuator are described. Saturation in the actuator is present and dealt with. The results of controlling the kiln with Direct Inverse Control and Additive Feedforward strategies are presented and compared. Proble...

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System (ANFIS). We examine the period 1950-2009, where we take as the in-sample or training period 1950-2005, ...

This paper proposes the use of artificial neural networks (feed forward multi-layer perceptron and Elman recurrent networks) in forecasting sales trends at retail by analyzing industry and manufacturer specific metrics along with national economic indicators. Relevant data drivers were gathered based on consultations with the manufacturer as well as experts in the fields of economics and financ...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

This paper demonstrates classification of PQ events utilizing wavelet transform (WT) energy features by artificial neural network (ANN) and SVM classifiers. The proposed scheme utilizes wavelet based feature extraction to be used for the artificial neural networks in the classification. Six different PQ events are considered in this study. Three types of neural network classifiers such as feed ...