BACKGROUND AND OBJECTIVE Artificial Neural Networks (ANNs) have recently been applied in situations where an analysis based on the logistic regression (LR) is a standard statistical approach; direct comparisons of the results, however, are seldom attempted. In this study, we compared both logistic regression models and feed-forward neural networks on the academic failure data set. METHODS The...

Supervised Artificial Neural Networks (ANN) are information processing systems that adapt their functionality as a result of exposure to input-output examples. To this end, there exist generic procedures and techniques, known as learning rules. The most widely used in the neural network context rely in derivative information, and are typically associated with the Multilayer Perceptron (MLP). Ot...

Structure of incremental neural network (IncNet) is controlled by growing and pruning to match the complexity of training data. Extended Kalman Filter algorithm and its fast version is used as learning algorithm. Bi-central transfer functions, more flexible than other functions commonly used in artificial neural networks, are used. The latest improvement added is the ability to rotate the conto...

Human milk contains all of the constituents that are required for the optimal growth and development of a neonate. It supports the development of brain, immune, and physiological systems. This study aimed to consider the significance of breast milk in preventing oxidative stress by comparing total antioxidant capacity (TAC) in breast and formula milk for premature infants, demonstrating the rel...

Human milk contains all of the constituents that are required for the optimal growth and development of a neonate. It supports the development of brain, immune, and physiological systems. This study aimed to consider the significance of breast milk in preventing oxidative stress by comparing total antioxidant capacity (TAC) in breast and formula milk for premature infants, demonstrating the rel...

This analysis principally focuses on the implementation of Radial basis function (RBF) and back propagation (BPA) algorithms for training artificial neural network (ANN) to get the optimum mixture of Hydro fluorocarbon (HFC) and organic compound (Hydrocarbons) for obtaining higher coefficient of Performances (COPs). The thermodynamical properties of mixed refrigerants are observed using REFPROP...

Precise knowledge ofthe amount of global solar radiation plays an important role in designing solar energy systems. In this study, by using 22-year meteorologicaldata, 19 empirical models were tested for prediction of the monthly mean daily global solar radiation in Tabriz. In addition, various Artificial Neural Network (ANN) models were designed for comparison with empirical models. For this p...

Streamflow forecasting has an important role in water resource management (e.g. flood control, drought management, reservoir design, etc.). In this paper, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) is used for long-term streamflow forecasting (monthly, seasonal) and moreover, cross-validation method (K-fold) is investigated to evaluate test-training data in the model.Then,...

an artificial neural network (ann) approach was used to model the wheat production. from an extensive data collection involving 40 farms in canterbury, new zealand, the average wheat production was estimated at 9.9 t ha-1. the final ann model developed was capable of predicting wheat production under different conditions and farming systems using direct and indirect technical factors. after exa...