Short-term daily precipitation forecasting with seasonally-integrated autoencoder

Short and Mid-Term Wind Power Plants Forecasting With ANN

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24...

Short-term quantitative precipitation forecasting using an object-based approach

Center for Hydrometeorology and Remote Sensing (CHRS), The Henry Samueli School of Engineering, Department of Civil and Environmental Engineering, University of California, Irvine, California, E/4130 Engineering Gateway, Irvine, CA 92697, United States NOAA/National Severe Storms Laboratory, Norman, Oklahoma, 120 David L. Boren Blvd., Rm. 4745, Norman, OK 73072, United States Department of Civi...

Short and Mid-Term Wind Power Plants Forecasting With ANN

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24...

Short - Term Load Forecasting

This paper presents a novel hybrid method for short-term load forecasting. The system comprises of two artificial neural networks (ANN), assembled in a hierarchical order. The first ANN is a multilayer perceptron (MLP) which functions as integrated load predictor (ILP) for the forecasting day. The output of the ILP is then fed to another, more complex MLP, which acts as an hourly load predictor...

Short-Term Weather Forecasting