Predicting Elite Triathlon Performance: A Comparison of Multiple Regressions and Artificial Neural Networks

Estimation of Soil Infiltration in Agricultural and Pasture Lands using Artificial Neural Networks and Multiple Regressions

Common methods to determine the soil infiltration need extensive time and are expensive. However, the existence of non-linear behaviors in soil infiltration makes it difficult to be modeled. With regards to the difficulties of direct measurement of soil infiltration, the use of indirect methods toestimate this parameter has received attention in recent years. Despite the existence of various th...

Predicting students' performance using artificial neural networks

Artificial intelligence has enabled the development of more sophisticated and more efficient student models which represent and detect a broader range of student behavior than was previously possible. In this work, we describe the implementation of a user-friendly software tool for predicting the students' performance in the course of “Mathematics” which is based on a neural network classifier....

Artificial neural networks: applications in predicting pancreatitis survival

Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

Artificial neural networks: applications in predicting pancreatitis survival

Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

Developing an Artificial Neural Networks Model for Predicting Output Energy and GHG Emission of Strawberry Production