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Fuzzy Rule Based Models Modification by New Data: Application to Flood Flow Forecasting

Author

Listed:
  • M. Akbari
  • A. Afshar
  • M. Sadrabadi

Abstract

Reconstruction and/or modification of an already existing fuzzy model with new data may improve system performances. As new data become available, adjusting the existing fuzzy rule-based model may present a challenging alternative to full model reconstruction. In this paper a fuzzy rule-based control model using a Takagi–Sugeno fuzzy system is presented and a model modification algorithm is developed which improves the performance of the initial model as new data become available. Proposed approach is applied to a flood flow forecasting case example and the results are compared with those forecasted using initially available and reconstructed models. Results show that the modified model outperforms the initial FRB model. Reconstructed model performs slightly better than the modified model; however, the reconstruction may not be justified in a real time flood forecasting system, considering the limitations on the available lead time. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • M. Akbari & A. Afshar & M. Sadrabadi, 2009. "Fuzzy Rule Based Models Modification by New Data: Application to Flood Flow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(12), pages 2491-2504, September.
    • Handle: RePEc:spr:waterr:v:23:y:2009:i:12:p:2491-2504
    DOI: 10.1007/s11269-008-9392-z
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    Citations

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    Cited by:

    1. Erica Camnasio & Gianfranco Becciu, 2011. "Evaluation of the Feasibility of Irrigation Storage in a Flood Detention Pond in an Agricultural Catchment in Northern Italy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1489-1508, March.
    2. Gokmen Tayfur & Vijay Singh, 2011. "Predicting Mean and Bankfull Discharge from Channel Cross-Sectional Area by Expert and Regression Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1253-1267, March.
    3. Gokmen Tayfur & Ata Nadiri & Asghar Moghaddam, 2014. "Supervised Intelligent Committee Machine Method for Hydraulic Conductivity Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 1173-1184, March.
    4. François Colin & Serge Guillaume & Bruno Tisseyre, 2011. "Small Catchment Agricultural Management Using Decision Variables Defined at Catchment Scale and a Fuzzy Rule-Based System: A Mediterranean Vineyard Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(11), pages 2649-2668, September.
    5. Mohammed Seyam & Faridah Othman, 2014. "The Influence of Accurate Lag Time Estimation on the Performance of Stream Flow Data-driven Based Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2583-2597, July.
    6. Zhangjun Liu & Shenglian Guo & Honggang Zhang & Dedi Liu & Guang Yang, 2016. "Comparative Study of Three Updating Procedures for Real-Time Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2111-2126, May.
    7. Seyed Akrami & Ahmed El-Shafie & Othman Jaafar, 2013. "Improving Rainfall Forecasting Efficiency Using Modified Adaptive Neuro-Fuzzy Inference System (MANFIS)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3507-3523, July.

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