Eyyüp Ensar BAŞAKIN, Mehmet ÖZGER, Necati Erdem ÜNAL

Gri Tahmin Yöntemi İle İstanbul Su Tüketiminin Modellenmesi

Mühendislik yapılarının ekonomik ve sürdürülebilir hizmet verebilmeleri, yapım öncesi titiz bir planlama gerektirmektedir. Uzun hizmet ömrü ve yüksek ilk yatırım maliyetleri sebebiyle ön planlama su yapılarında ayrı bir önem taşır. Projelendirilecek su yapısının hangi boyut ve özellikte olması gerektiği, su tüketim miktarları ile ilişkilidir. Gelecekte gerçekleşmesi düşünülen su tüketim değerinin tespiti bu yapıların inşa sürecine önemli katkılar sunmaktadır. Ancak bazı bölgelerde geçmişte kullanılan su miktarına ait ölçümlerdeki yetersizlik veya eksik kayıtlar sebebiyle tahmin yapmak zorlaşmaktadır. Klasik tahmin yöntemleri belirli bir sayının altında veri ile sağlıklı performans sergileyemezler. Geçmiş kayıtların az olduğu durumlarda ise Gri Tahmin yöntemi en çok başvurulan yöntemlerden biridir. Bu çalışmada, güncel bir yöntem olan Gri Tahmin yöntemi kullanılarak İstanbul ilinin yıllık su tüketim değerleri tahmin edilmeye çalışılmıştır. Gri Tahmin yöntemlerinin sonuçları istatistiksel başarı kriterleri yardımıyla test edilmiş ve hidrolojide kullanımının mümkün olduğu görülmüştür.

Anahtar Kelimeler:

Gri tahmin, su tüketimi, hidroloji, zaman serisi, matematik model

Water Consumption Model Of Istanbul City By Gray Prediction Method

Engineering structures require precise planning before its construction to provide economical and sustainable service. Due to long service life and high initial investment costs, preliminary planning is of particular importance for water structures. The size and type of the water structure to be projected is highly related to the amount of water consumption rate. The determination of water consumption rate which is considered to be realized in the future provides an important contribution to the construction process of these special structures. However, in some regions it is difficult to estimate the water demand because of inadequacies or missing records in previous water consumption rates. Classical prediction methods cannot perform well with limited number of data. Gray Prediction Model is one of the most commonly used methods when there are few records. In this study, annual water consumption rates of the province of Istanbul were estimated by using Gray Prediction Model which is a contemporary method. The results of the Gray Prediction Model was tested with the help of statistical error criteria and it was found out that this method gives satisfactory results in hydrology area even if number of data is limited.

Keywords:

Gray prediction, water consumption, hydrology, time series, mathematical model,

___

[1] Maidment, D. R., and Parzen, E., "Cascade model of monthly municipal water use." Water Resources Research, 20(1): 15-23, (1984)
[2] Dziegielewski, B., and Boland, J. J., "Forecasting urban water use: the iwr-main model1." JAWRA Journal of the American Water Resources Association, 25(1): 101-109, (1989)
[3] Altunkaynak, A., Özger, M., and Çakmakci, M., "Water consumption prediction of istanbul city by using fuzzy logic approach." Water Resources Management, 19(5): 641-654, (2005)
[4] Altunkaynak, A., and Nigussie, T. A., "Monthly water consumption prediction using season algorithm and wavelet transform;based models." Journal of Water Resources Planning and Management, 143(6): 04017011, (2017)
[5] Firat, M., Turan, M. E., and Yurdusev, M. A., "Comparative analysis of fuzzy inference systems for water consumption time series prediction." Journal of Hydrology, 374(3): 235-241, (2009)
[6] Adamowski, J., and Karapataki, C., "Comparison of multivariate regression and artificial neural networks for peak urban water-demand forecasting: evaluation of different ann learning algorithms." Journal of Hydrologic Engineering, 15(10): 729-743, (2010)
[7] Nasseri, M., Moeini, A., and Tabesh, M., "Forecasting monthly urban water demand using Extended Kalman Filter and Genetic Programming." Expert Systems with Applications, 38(6): 7387-7395, (2011)
[8] Zhang, D., Ni, G., Cong, Z., Chen, T., and Zhang, T., "Statistical interpretation of the daily variation of urban water consumption in Beijing, China." Hydrological Sciences Journal, 59(1): 181-192, (2013)
[9] Liu, Y., Zhao, J., and Wang, Z., "Identifying determinants of urban water use using data mining approach." Urban Water Journal, 12(8): 618-630, (2014)
[10] Zhou, S. L., McMahon, T. A., Walton, A., and Lewis, J., "Forecasting daily urban water demand: a case study of Melbourne." Journal of Hydrology, 236(3): 153-164, (2000)
[11] Trivedi, H. V., and Singh, J. K., "Application of grey system theory in the development of a runoff prediction model." Biosystems Engineering, 92(4): 521-526, (2005)
[12] Yu, P.-S., Chen, C.-J., and Chen, S.-J., "Application of gray and fuzzy methods for rainfall forecasting." Journal of Hydrologic Engineering, 5(4): 339-345, (2000)
[13] Ho, J.-Y., and Lee, K., "Grey forecast rainfall with flow updating algorithm for real-time flood forecasting." Water, 7(5): 1840, (2015).
[14] Lin, Y.-H., Chiu, C.-C., Lee, P.-C., and Lin, Y.-J., "Applying fuzzy grey modification model on inflow forecasting." Engineering Applications of Artificial Intelligence, 25(4): 734-743, (2012)
[15] Chou, C.-m., "Applying multi-resolution analysis to differential hydrological grey models with dual series." Journal of Hydrology, 332(1): 174-186, (2007)
[16] Wang Yu-lu, Y. Y.-b., Yuan Xiao-hui , Zhang Miao "A modified nonlinear grey bernoulli model used for water consumption prediction." March 2017 Singapore International Conferences. (2017)
[17] Nash, J. E., and Sutcliffe, J. V., "River flow forecasting through conceptual models part I — A discussion of principles." Journal of Hydrology, 10(3): 282-290, (1970)