Objective: Breast cancer is one of the most common cancers affecting women. Both physicians and patients have concerned about breast cancer survivability. Many researchers have studied the breast cancer survivability applying artificial nerural network model (ANN). Usually ANN model outperformed in classification of breast cancer survivability than other models such as logistic regression, Baye...

global positioning system (gps) signals provide valuable information about ionosphere physical structure. using these signals, can be derived total electron content (tec) for each line of sight between the receiver and the satellite. for historic and other sparse data sets, the reconstruction of tec images is often performed using multivariate interpolation techniques. recently it has become cl...

In this paper a novel technique is proposed for the estimation of resonant frequency of coaxial feed equilateral triangular microstrip patch antenna. The major advantage of the proposed approach is that, after proper training, proposed neural model completely bypasses the repeated use of complex i terative process for calculation of resonant frequency, thus resulting in an extremely fast soluti...

This paper presents an alternative method using artificial neural network (ANN) to develop a scheduling scheme which is used to determine the makespan or cycle time of a group of jobs going through a series of stages or workstations. The common conventional method uses mathematical programming techniques and presented in Gantt charts forms. The contribution of this paper is in three fold. First...

introduction: evaporation and evapotranspiration are two major components of hydrological cycle which are very important for agricultural studies as well as water resources management. so far, various methods have been addressed for the estimation of daily reference crop evapotranspiration (et0). among them, fao penman-montieth 56 (pmf-56) (allen et al., 1998) is widely used as a standard metho...

The paper describes an artificial neural network (ANN) model to predict the height of destressed zone (HDZ) which is taken as equivalent to the combined height of caved and fractured zones above the mined panel in longwall mining. For this, the suitable datasets have been collected from the literatures and prepared for modeling. The data were used to construct a multilayer perceptron (MLP) netw...

artificial neural networks (ann) have shown to be a powerful tool for system modeling in a wide range of applications. the focus of this study is on neural network applications to data analysis in egg production. an ann model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variabl...

rainfall-runoff relationship is very important in many fields of hydrology such as water supply and water resourcemanagement and there are many models in this field. among these models, the artificial neural network (ann) wasfound suitable for processing rainfall-runoff and opened various approaches in hydrological modeling. in addition,anns are quick and flexible approaches which provide very ...

This paper describes the comparison of Artificial Intelligence (AI) based rotor position estimation techniques for Switched Reluctance Motor (SRM) with respect to its execution time in Digital Signal Processor (DSP) TMS320F2812. The various networks of Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System ( ANFIS) structures are trained for mapping the nonlinear current-flux...