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Estimation of relative humidity based on artificial neural network approach in the Aegean Region of Turkey

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Abstract

The aim of this study is to estimate the monthly mean relative humidity (MRH) values in the Aegean Region of Turkey with the help of the topographical and meteorological parameters based on artificial neural network (ANN) approach. The monthly MRH values were calculated from the measurement in the meteorological observing stations established in Izmir, Mugla, Aydin, Denizli, Usak, Manisa, Kutahya and Afyonkarahisar provinces between 2000 and 2006. Latitude, longitude, altitude, precipitation and months of the year were used in the input layer of the ANN network, while the MRH was used in output layer of the network. The ANN model was developed using MATLAB software, and then actual values were compared with those obtained by ANN and multi-linear regression methods. It seemed that the obtained values were in the acceptable error limits. It is concluded that the determination of relative humidity values is possible at any target point of the region where the measurement cannot be performed.

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Acknowledgments

The authors would like to express their appreciation to the Turkish State Meteorological Services (TSMS) for providing the data.

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Authors and Affiliations

  1. Adana Vocational School of Higher Education, Cukurova University, 01160, Adana, Turkey

    Abdulkadir Yasar, Erdoğan Simsek, Mehmet Bilgili, Ahmet Yucel & Ilhami Ilhan

Authors
  1. Abdulkadir Yasar
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  2. Erdoğan Simsek
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  3. Mehmet Bilgili
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  4. Ahmet Yucel
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  5. Ilhami Ilhan
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Corresponding author

Correspondence to Abdulkadir Yasar.

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Responsible Editor: L. Gimeno.

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Yasar, A., Simsek, E., Bilgili, M. et al. Estimation of relative humidity based on artificial neural network approach in the Aegean Region of Turkey. Meteorol Atmos Phys 115, 81–87 (2012). https://doi.org/10.1007/s00703-011-0168-2

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  • DOI: https://doi.org/10.1007/s00703-011-0168-2

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