Computational Intelligence techniques have been proposed as an efficient tool for modeling and forecasting in recent years and in various applications. Water is a basic need and as...
Ishmael S. Msiza, Fulufhelo Vincent Nelwamondo, Ts...
The accuracy of a model to forecast a time series diminishes as the prediction horizon increases, in particular when the prediction is carried out recursively. Such decay is faster...
Abstract. Local air quality forecasting can be made on the basis of meteorological and air pollution time series. Such data contain redundant information. Partial mutual informatio...
Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no expli...
Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C...
In this work, we propose to use the Zoomed-Ranking approach to ranking and selecting Artificial Neural Network (ANN) models for time series forecasting. Given a time series to fo...