Araştırma Makalesi

Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey

Cilt: 13 Sayı: 3 31 Aralık 2020
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Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey

Öz

This study aimed to determine the most suitable local geoid model based on 641 GNSS/leveling points within the borders of Kars Province in eastern Turkey using the generalized regression neural network (GRNN), weighted average (WA), multiquadric (MQ), inverse multiquadric (IMQ) function, and local polynomial (LP) method. Among these methods used in local geoid determination, the studies conducted with the GRNN method are very limited in the literature. To test the performance of the model, 169 GNSS/leveling points were selected as test data. When selecting the reference and test points, care was taken to ensure that the distribution of the points was homogeneous. The criteria of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) were used to assess the accuracy and error rates of the results achieved using the different methods. The analysis showed that the GRNN yielded better results than other interpolation methods (RMSE = 1.215 cm, MAE = 0.467 cm, R2 = 0.99980).

Anahtar Kelimeler

Kaynakça

  1. Albayrak, M., Özlüdemir, M. T., Aref, M. M., Halicioglu, K. 2020. “Determination of Istanbul geoid using GNSS/levelling and valley cross levelling data”, Geodesy and Geodynamics, 11(3), 163-173.
  2. Becker, M. 2012. “Geodesy”, Springer handbook of geographic information, Springer, Springer Heidelberg Dordrecht London New York, 185-208.
  3. Bolat, S. 2013 “Lokal Jeoid Belirleme Yöntemleri: Samsun İli Örneği”, Yüksek Lisans Tezi, Ondokuz Mayıs Üniversitesi Fen Bilimleri Enstitüsü, Samsun, 30-32.
  4. Cakir, L. and Yilmaz, N. 2014. “Polynomials, radial basis functions and multilayer perceptron neural network methods in local geoid determination with GPS/levelling”, Measurement, 57, 148-153.
  5. Carlson, R.E. and Foley, T.A. 1991. “The Parameter R2 in Multiquadric Interpolation”, Computers & Mathematics with Applications, 21, 29-42.
  6. Ceylan, A., Üstün, A., Doğanalp, S., Gürses, H.B. 2011. “Karayolu ve Demiryolu Projelerinde Ortometrik Yükseklik Hesabı: En küçük Kareler ile Kollokasyon”, 13. Türkiye Harita Bilimsel ve Teknik Kurultayı, TMMOB Harita ve Kadastro Mühendisleri Odası, Ankara, 1-8.
  7. Doganalp, S. 2016. “Geoid height computation in strip-area project by using least-squares collocation”, Acta Geodyn. Geomater, 13(2), 182.
  8. Doganalp, S. and Selvi, H.Z. 2015. “Local geoid determination in strip area projects by using polynomials, least-squares collocation and radial basis functions”, Measurement, 73, 429-438.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

31 Aralık 2020

Gönderilme Tarihi

4 Aralık 2020

Kabul Tarihi

27 Aralık 2020

Yayımlandığı Sayı

Yıl 2020 Cilt: 13 Sayı: 3

Kaynak Göster

APA
Akar, A., & Konakoglu, B. (2020). Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey. Erzincan University Journal of Science and Technology, 13(3), 1424-1438. https://doi.org/10.18185/erzifbed.835878
AMA
1.Akar A, Konakoglu B. Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey. Erzincan University Journal of Science and Technology. 2020;13(3):1424-1438. doi:10.18185/erzifbed.835878
Chicago
Akar, Alper, ve Berkant Konakoglu. 2020. “Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey”. Erzincan University Journal of Science and Technology 13 (3): 1424-38. https://doi.org/10.18185/erzifbed.835878.
EndNote
Akar A, Konakoglu B (01 Aralık 2020) Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey. Erzincan University Journal of Science and Technology 13 3 1424–1438.
IEEE
[1]A. Akar ve B. Konakoglu, “Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey”, Erzincan University Journal of Science and Technology, c. 13, sy 3, ss. 1424–1438, Ara. 2020, doi: 10.18185/erzifbed.835878.
ISNAD
Akar, Alper - Konakoglu, Berkant. “Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey”. Erzincan University Journal of Science and Technology 13/3 (01 Aralık 2020): 1424-1438. https://doi.org/10.18185/erzifbed.835878.
JAMA
1.Akar A, Konakoglu B. Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey. Erzincan University Journal of Science and Technology. 2020;13:1424–1438.
MLA
Akar, Alper, ve Berkant Konakoglu. “Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey”. Erzincan University Journal of Science and Technology, c. 13, sy 3, Aralık 2020, ss. 1424-38, doi:10.18185/erzifbed.835878.
Vancouver
1.Alper Akar, Berkant Konakoglu. Local geoid determination using a generalized regression neural network and interpolation methods: A case study in Kars, Turkey. Erzincan University Journal of Science and Technology. 01 Aralık 2020;13(3):1424-38. doi:10.18185/erzifbed.835878

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