Modellling of rainfall runoff relation with artificial neural network methods for Seyhan basin
2012
0 views
0 downloads
Advisor: Yrd. Doç. Dr. Hatice Çağatay
Abstract (EN)
It is very important to obtain reliable estimation and modelling of runoff in planning and designing of water resources. The current study aims to model rainfall-runoff relation using Artificial Neural Networks (ANN). In this study, MATLAB R2008a was used as a modelling tool. Seyhan Basin was selected for application. Previous rainfall-runoff observations were used in estimation of runoff. In this study, ANN method of the Feed Forward Back Propagation Neural Network (FFBPNN) was adopted and results were compared with those of Multi Linear Regression (MLR) method. In conclusion, FFBPNN method provides better results than results of MLR method.
Author
Evren Turhan
How to Cite
Evren Turhan (Master Thesis). Modellling of rainfall runoff relation with artificial neural network methods for Seyhan basin, 2012, Çukurova University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Çukurova University
- The effects of collaborative video-blog projects on Turkish EFL students' linguistic and digital literacy skills(2025)
- An investigation of violent and nonviolent adolescent' families in terms in terms of family fuctioning, anger and anger expression(2006)
- Adolescents who have single parents family and full family were compared in respect to their life satisfaction and quality of life(2009)
- Credit risk management in banking sector: An application of variables determining credit risk in Turkish banking sector(2011)
- Investigation of psychological symptom levels in adolescents according to gender and family functions(2013)
- Assessing morphological and genetic diversity among traditional African eggplant landraces and detecting salt tolerance and anther culture performance of selected accessions(2022)
