The accurate estimation of meteorological profiles employing ANNs.
The lack of meteorological measurements at a location of interest (target location) constitutes a problem that is crucial for the purposes of both weather forecasting and energy system design/validation. This paper constitutes a pilot study for the accurate estimation of meteorological values at a target location employing the meteorological measurements collected at a nearby (reference) location. Artificial neural networks are investigated and compared with traditional estimation methods such as linear models of first and higher orders and the non-linear model. The significance of the improvement obtained via the estimation--and especially the artificial neural network approach--over simply considering the measurements at the reference location is demonstrated in a number of energy applications.
Tambouratzis
Tatiana
T
Institute of Nuclear Technology--Radiation Protection, NCSR Demokritos, Aghia Paraskevi 153 10, Athens, Greece. tatiana@ipta.demokritos.gr
Gazela
Myrsini
M
D000465:Algorithms; D001185:Artificial Intelligence; D005544:Forecasting / Q000379:methods; D016014:Linear Models; D008685:Meteorological Concepts; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D015203:Reproducibility of Results