Prediction of Long-term Monthly Temperature and Rainfall in Turkey

Bilgil M., ŞAHİN B.

ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, cilt.32, sa.1, ss.60-71, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 1
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1080/15567030802467522
  • Dergi Adı: ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.60-71
  • Anahtar Kelimeler: artificial neural network, prediction, rainfall, temperature, ARTIFICIAL NEURAL-NETWORK
  • Çukurova Üniversitesi Adresli: Evet

Özet

In this study, artificial neural networks were applied to predict the long-term monthly temperature and rainfall at any target point of Turkey based on the use of the neighboring measuring stations data. For this purpose, meteorological data measured by the Turkish State Meteorological Service between the years 1975 and 2006 from 76 measuring stations were used a straining (59 stations) and testing (17 stations) data. Four neurons which receive input signals of latitude, longitude, altitude, and month were used in the input layer of the network. Two neurons, which produce corresponding out put signals of the long-term monthly temperature and rainfall, were utilized in the output layer of the network. Finally, the values determined by the artificial neural network model were compared with the actual data. Errors obtained in this model are well with in acceptable limits.