6533b832fe1ef96bd129a500

RESEARCH PRODUCT

Daily Peak Temperature Forecasting with Elman Neural Networks

M. PerniceSalvatore GaglioSalvatore Vitabile

subject

Artificial neural networkComputer sciencebusiness.industryLoad forecastingWeather forecastingHumiditycomputer.software_genreRpropBackpropagationStatisticsartificial neural networkTemperature forecastingPrecipitationWest coastArtificial intelligencebusinesscomputer

description

This work presents a forecaster based on an Elman artificial neural network trained with resilient backpropagation algorithm for predicting the daily peak temperatures one day ahead. The available time series was recorded at Petrosino (TP), in the west coast of Sicily, Italy and it is composed by temperature (min and max values), the humidity (min and max values) and the rainfall value between January 1st, 1995 and May 14th, 2003. Performances and reliabilities of the proposed model were evaluated by a number of measures, comparing different neural models. Experimental results show very good prediction performances.

yearjournalcountryeditionlanguage
2005-02-28
10.1109/ijcnn.2004.1381091http://hdl.handle.net/10447/4815