Author/Authors :
Ilaria Bertini a، نويسنده , , Francesco Ceravolo a، نويسنده , , Marco Citterio a، نويسنده , , Matteo De Felice a، نويسنده , , b، نويسنده , ,
Biagio Di Pietra a، نويسنده , , Francesca Margiotta a، نويسنده , , Stefano Pizzuti a، نويسنده , , *، نويسنده , , Giovanni Puglisi، نويسنده ,
Abstract :
This paper proposes a hybrid approach based on soft computing techniques in order to estimate monthly and daily ambient temperature.
Indeed, we combine the back-propagation (BP) algorithm and the simple Genetic Algorithm (GA) in order to effectively train
artificial neural networks (ANN) in such a way that the BP algorithm initialises a few individuals of the GA’s population. Experiments
concerned monthly temperature estimation of unknown places and daily temperature estimation for thermal load computation. Results
have shown remarkable improvements in accuracy compared to traditional methods.
2010 Elsevier Ltd. All rights reserved
