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Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules

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  • A. kumar
  • Manish Goyal
  • C. Ojha
  • R. Singh
  • P. Swamee
  • R. Nema

Abstract

Optimal use of scarce water resources is the prime objective for water resources development projects in the developing country like India. Optimal releases have been generally expressed as a function of reservoir state variables and hydrologic inputs by a relationship which ultimately allows the policy/water managers to determine the water to be released as a function of available information. Optimal releases were obtained by using optimal control theory with inflow series and revised reservoir characteristics such as elevation area capacity table, zero elevation level as input in this study. Operating rules for reservoir were developed as a function of demand, water level and inflow. Artificial Neural Network (ANN) with back propagation algorithm, Fuzzy Logic and decision tree algorithms such as M5 and REPTree were used for deriving the operating rules using the optimal releases for an irrigation and power supply reservoir, located in northern India. It was found that fuzzy logic model performed well compared to other soft computing techniques such as ANN, M5P and REPTree investigated in this study. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • A. kumar & Manish Goyal & C. Ojha & R. Singh & P. Swamee & R. Nema, 2013. "Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 911-925, February.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:3:p:911-925
    DOI: 10.1007/s11269-012-0225-8
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    References listed on IDEAS

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    1. A. Cancelliere & G. Giuliano & A. Ancarani & G. Rossi, 2002. "A Neural Networks Approach for Deriving Irrigation Reservoir Operating Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(1), pages 71-88, February.
    2. Xinyuan Liu & Shenglian Guo & Pan Liu & Lu Chen & Xiang Li, 2011. "Deriving Optimal Refill Rules for Multi-Purpose Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 431-448, January.
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    4. Manish Goyal & C. Ojha, 2011. "Estimation of Scour Downstream of a Ski-Jump Bucket Using Support Vector and M5 Model Tree," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2177-2195, July.
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    3. Guang Yang & Shenglian Guo & Pan Liu & Xiaofeng Liu & Jiabo Yin, 2020. "Heuristic Input Variable Selection in Multi-Objective Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 617-636, January.
    4. Chang-ming Ji & Ting Zhou & Hai-tao Huang, 2014. "Operating Rules Derivation of Jinsha Reservoirs System with Parameter Calibrated Support Vector Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2435-2451, July.
    5. Gokmen Tayfur & Luca Brocca, 2015. "Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3519-3533, August.
    6. Mahmoud Mohammad Rezapour Tabari & Mohsen Mazak Mari, 2016. "The Integrated Approach of Simulation and Optimization in Determining the Optimum Dimensions of Canal for Seepage Control," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1271-1292, February.
    7. Sabah Fayaed & Ahmed El-Shafie & Othman Jaafar, 2013. "Integrated Artificial Neural Network (ANN) and Stochastic Dynamic Programming (SDP) Model for Optimal Release Policy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3679-3696, August.
    8. Benya Suntaranont & Somrawee Aramkul & Manop Kaewmoracharoen & Paskorn Champrasert, 2020. "Water Irrigation Decision Support System for Practical Weir Adjustment Using Artificial Intelligence and Machine Learning Techniques," Sustainability, MDPI, vol. 12(5), pages 1-18, February.
    9. Guang Yang & Shenglian Guo & Liping Li & Xingjun Hong & Le Wang, 2016. "Multi-Objective Operating Rules for Danjiangkou Reservoir Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1183-1202, February.
    10. Nazak Rouzegari & Yousef Hassanzadeh & Mohammad Taghi Sattari, 2019. "Using the Hybrid Simulated Annealing-M5 Tree Algorithms to Extract the If-Then Operation Rules in a Single Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3655-3672, August.
    11. Izabela Rojek, 2014. "Models for Better Environmental Intelligent Management within Water Supply Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3875-3890, September.
    12. Liping Li & Pan Liu & David Rheinheimer & Chao Deng & Yanlai Zhou, 2014. "Identifying Explicit Formulation of Operating Rules for Multi-Reservoir Systems Using Genetic Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1545-1565, April.
    13. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.

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    More about this item

    Keywords

    Reservoir operation; Neural networks; Fuzzy logic; M5; REPTree;
    All these keywords.

    JEL classification:

    • M5 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics

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