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Predicting Monthly River Flows by Genetic Fuzzy Systems

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  • Mustafa Turan
  • Mehmet Yurdusev

Abstract

Reliable flow forecasts are key to developing river regulation schemes such as reservoirs. River flow prediction has conventionally been undertaken by physical and black-box models. Several black-box type models have been employed to achieve this end. Of these, genetic fuzzy systems have been used in this study as they have relatively attracted limited attention to date. Genetic-fuzzy systems are the fuzzy systems that have the capability of learning and tuning by Genetic Algorithms. Employing two different fuzzy inference systems, a case study on Gediz river basin has been performed in an attempt to find a suitable genetic fuzzy system for flow prediction. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Mustafa Turan & Mehmet Yurdusev, 2014. "Predicting Monthly River Flows by Genetic Fuzzy Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4685-4697, October.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:13:p:4685-4697
    DOI: 10.1007/s11269-014-0767-z
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    References listed on IDEAS

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    1. Ozgur Kisi & Alireza Nia & Mohsen Gosheh & Mohammad Tajabadi & Azadeh Ahmadi, 2012. "Intermittent Streamflow Forecasting by Using Several Data Driven Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(2), pages 457-474, January.
    2. Mehdi Rezaeian Zadeh & Seifollah Amin & Davar Khalili & Vijay Singh, 2010. "Daily Outflow Prediction by Multi Layer Perceptron with Logistic Sigmoid and Tangent Sigmoid Activation Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2673-2688, September.
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    4. Alpaslan Yarar, 2014. "A Hybrid Wavelet and Neuro-Fuzzy Model for Forecasting the Monthly Streamflow Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 553-565, January.
    5. Ozgur Kisi & Taner Cengiz, 2013. "Fuzzy Genetic Approach for Estimating Reference Evapotranspiration of Turkey: Mediterranean Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3541-3553, August.
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    2. Zaher Mundher Yaseen & Ozgur Kisi & Vahdettin Demir, 2016. "Enhancing Long-Term Streamflow Forecasting and Predicting using Periodicity Data Component: Application of Artificial Intelligence," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4125-4151, September.
    3. Zaher Mundher Yaseen & Minglei Fu & Chen Wang & Wan Hanna Melini Wan Mohtar & Ravinesh C. Deo & Ahmed El-shafie, 2018. "Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1883-1899, March.
    4. Huaping Huang & Zhongmin Liang & Binquan Li & Dong Wang & Yiming Hu & Yujie Li, 2019. "Combination of Multiple Data-Driven Models for Long-Term Monthly Runoff Predictions Based on Bayesian Model Averaging," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3321-3338, July.
    5. Reza Mohammadpour & Aminuddin Ab. Ghani & Mohammadtaghi Vakili & Tooraj Sabzevari, 2016. "Prediction of temporal scour hazard at bridge abutment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1891-1911, February.
    6. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Xiao-Yun Chen, 2015. "Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2655-2675, June.
    7. Reza Mohammadpour & Aminuddin Ghani & Mohammadtaghi Vakili & Tooraj Sabzevari, 2016. "Prediction of temporal scour hazard at bridge abutment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1891-1911, February.
    8. Mohammad Nikoo & Nafise Khorramshokouh & Shahryar Monghasemi, 2015. "Optimal Design of Detention Rockfill Dams Using a Simulation-Based Optimization Approach with Mixed Sediment in the Flow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5469-5488, December.

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