A study using 51 wheat, 56 barley and 34 oat grain samples was conducted to investigate the feasibility of predicting the apparent metabolizable energy (AME) value of these cereals for poultry. Stepwise regression analyses were performed to evaluate the relationship of AME with starch, ether extract (EE), crude fiber (CF), soluble sugar (SS), ash and crude protein (CP) (for wheat and barley gra...

Background: We designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the Artificial Neural Network (ANN). Materials and methods: The ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. Each patient’s record consisted of 6 subjec...

This paper examined bankruptcy predictive accuracy of five statistics models-discriminant analysis logistic regression, probit regression, neural networks, support vector machine (SVM), and genetic-based SVM (GA-SVM) that influenced by variable selection. Empirical results indicate that the SVM-based models are very promising models for predicting financial failure, in terms of both best predic...

The paper presents a hybrid model of an Artificial Neural Network (ANN) and Genetic Algorithm (GA) for modeling of a hybrid laser welding process. This model is employed for the prediction and optimization of penetration depth with corresponding process parameters. A single program developed for the purpose initially establishes an optimized ANN architecture using a Back-Propagation Neural Netw...

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regre...

The accurate prediction of air temperature is important in many areas of decision-making including agricultural management, transportation and energy management. Previous research has focused on the development of artificial neural network (ANN) models to predict air temperature from one to twelve hours in advance. The inputs to these models included a constant duration of prior data with a fix...

Bedrock unconfined compressive strength (UCS) is a key parameter in designing thegeosciences and building related projects comprising both the underground and surface rock structures. Determination of rock UCS using standard laboratory tests is a complicated, expensive, and time-consuming process, which requires fresh core specimens. However, preparing fresh cores is not always possible, especi...