A Neural Network Model For The Estimation Of
Bioclimatic Indexes
Author(s)
F. Patania, A. Gagliano, R. Caponetto, F. Nocera & A. Galesi
Abstract
Many researches have highlighted the influence of climate on mortality, showing
a high increase in mortality in the summer time during \“heat waves”, periods of
very high temperature and humidity levels.
The bioclimatic indexes are used in urban climate studies to describe the level
of thermal sensation that a person experiences due to the modified climatic
conditions of an urban area.
The index provides a meaningful and realistic indicator that can not only be
used as an information as to how hot it feels, but also as a readily identifiable
warning for individuals subject to the physiological dangers of heat exposure.
The authors have developed a methodology that, by means of the Neural
Network (NN), permits one to predict the values of meteorological data and then
the calculation of the bioclimatic indexes.
The meteorological data required for the calculation of the bioclimatic index
concerning hourly values of air temperature, relative humidity, wind speed have
been used according to the records of the meteorological station of the Pergusa
Lake (EN), for the year from 2003 to 2006
NN-estimated, the bioclimatic indexes values were compared with coincident
bioclimatic indexes values obtained from air temperature and relative humidity
observations recorded at standard meteorological stations.
Statistical analysis showed a good agreement between the NN-estimated and
the station-observed bioclimatic indexes values, with a root mean square error
(RMSE) < 1%.
Keywords
heat-waves, bioclimatic index, Neural Network
Related Book
Other papers in this volume
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