Prediction by using Artificial Neural Networks and Box-Jenkins methodologies: Comparison Study

Prediction of Gas Lift Parameters Using Artificial Neural Networks

Multivariate Forecasting of Electricity Production using Neural Network and Box-Jenkins Methodologies

The aim of this paper is to prove the validity of an alternative prediction technique to another classical one, which is Box-Jenkins methodology, in order to produce multivariate prediction. In particular, one-step ahead forecasts will be obtained for two time series: thermic and hydraulic power production. These forecasts are based on the past values of those series.

PRECIPITATION PREDICTION USING ARTIFICIAL NEURAL NETWORKS by

Precipitation, in meteorology, is defined as any product, liquid or solid, of atmospheric water vapor that is accumulated onto the earth’s surface. Water, and thus precipitation, has a major impact on our daily livelihood. As such, the uncertainty of both the future occurrence and amount of precipitation can have a negative impact on many sectors of our economy, especially agriculture. There is...

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...