One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling
The present study, deals with the 24-hour prognosis of the outdoor biometeorological conditions in an urban monitoring site within the Greater Athens area, Greece. For this purpose, artificial neural networks (ANNs) modelling techniques are applied in order to predict the maximum and the minimum val...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2013/538508 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832563694598356992 |
|---|---|
| author | K. P. Moustris P. T. Nastos A. G. Paliatsos |
| author_facet | K. P. Moustris P. T. Nastos A. G. Paliatsos |
| author_sort | K. P. Moustris |
| collection | DOAJ |
| description | The present study, deals with the 24-hour prognosis of the outdoor biometeorological conditions in an urban monitoring site within the Greater Athens area, Greece. For this purpose, artificial neural networks (ANNs) modelling techniques are applied in order to predict the maximum and the minimum value of the physiologically equivalent temperature (PET) one day ahead as well as the persistence of the hours with extreme human biometeorological conditions. The findings of the analysis showed that extreme heat stress appears to be 10.0% of the examined hours within the warm period of the year, against extreme cold stress for 22.8% of the hours during the cold period of the year. Finally, human thermal comfort sensation accounts for 81.8% of the hours during the year. Concerning the PET prognosis, ANNs have a remarkable forecasting ability to predict the extreme daily PET values one day ahead, as well as the persistence of extreme conditions during the day, at a significant statistical level of . |
| format | Article |
| id | doaj-art-34d27baf185242d7aae35bef693c9d36 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-34d27baf185242d7aae35bef693c9d362025-02-03T01:12:40ZengWileyAdvances in Meteorology1687-93091687-93172013-01-01201310.1155/2013/538508538508One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks ModelingK. P. Moustris0P. T. Nastos1A. G. Paliatsos2Department of Mechanical Engineering, Technological Educational Institute of Piraeus, 250 Thivon and P. Ralli Street, 122 44 Aegaleo, GreeceLaboratory of Climatology and Atmospheric Environment, Faculty of Geology and Geoenvironment, University of Athens, Panepistimiopolis, 157 84 Athens, GreeceGeneral Department of Mathematics, Technological Educational Institute of Piraeus, 250 Thivon and P. Ralli Street, 122 44 Aegaleo, GreeceThe present study, deals with the 24-hour prognosis of the outdoor biometeorological conditions in an urban monitoring site within the Greater Athens area, Greece. For this purpose, artificial neural networks (ANNs) modelling techniques are applied in order to predict the maximum and the minimum value of the physiologically equivalent temperature (PET) one day ahead as well as the persistence of the hours with extreme human biometeorological conditions. The findings of the analysis showed that extreme heat stress appears to be 10.0% of the examined hours within the warm period of the year, against extreme cold stress for 22.8% of the hours during the cold period of the year. Finally, human thermal comfort sensation accounts for 81.8% of the hours during the year. Concerning the PET prognosis, ANNs have a remarkable forecasting ability to predict the extreme daily PET values one day ahead, as well as the persistence of extreme conditions during the day, at a significant statistical level of .http://dx.doi.org/10.1155/2013/538508 |
| spellingShingle | K. P. Moustris P. T. Nastos A. G. Paliatsos One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling Advances in Meteorology |
| title | One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling |
| title_full | One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling |
| title_fullStr | One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling |
| title_full_unstemmed | One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling |
| title_short | One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling |
| title_sort | one day prediction of biometeorological conditions in a mediterranean urban environment using artificial neural networks modeling |
| url | http://dx.doi.org/10.1155/2013/538508 |
| work_keys_str_mv | AT kpmoustris onedaypredictionofbiometeorologicalconditionsinamediterraneanurbanenvironmentusingartificialneuralnetworksmodeling AT ptnastos onedaypredictionofbiometeorologicalconditionsinamediterraneanurbanenvironmentusingartificialneuralnetworksmodeling AT agpaliatsos onedaypredictionofbiometeorologicalconditionsinamediterraneanurbanenvironmentusingartificialneuralnetworksmodeling |