Caspian Sea level prediction using satellite altimetry by artificial neural networks

Glucose Level Prediction Using Artificial Neural Networks

The advanced treatment of the type I diabetes mellitus through closed-loop systems, such as artificial pancreas is one of today’s greatest challenges. In this work the authors have tried to develop a predictive method which can be incorporated in an optimal system for blood glucose-insulin regulation. Using the neural network approach it is possible to compose a prediction model, very useful to...

Prediction of Gas Lift Parameters Using Artificial Neural Networks

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...

Sea Level Anomaly Prediction using Recurrent Neural Networks

Sea level change, one of the most dire impacts of anthropogenic global warming, will affect a large amount of the world’s population. However, sea level change is not uniform in time and space, and the skill of conventional prediction methods is limited due to the ocean’s internal variability on timescales from weeks to decades. Here we study the potential of neural network methods which have b...

Prediction the Return Fluctuations with Artificial Neural Networks' Approach

Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study incl...