Fuzzy rule-based modeling of reservoir operation

被引:128
|
作者
Shrestha, BP
Duckstein, L
Stakhiv, EZ
机构
[1] UNIV ARIZONA, DEPT SYST & IND ENGN, TUCSON, AZ 85721 USA
[2] USA, IWR, POLICY & SPEC STUDIES DIV, CORPS ENGINEERS, FT BELVOIR, VA 22060 USA
关键词
D O I
10.1061/(ASCE)0733-9496(1996)122:4(262)
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A fuzzy rule-based model is constructed to derive operation rules for a multipurpose reservoir. The case study of the Tenkiller Lake in Oklahoma illustrates the methodology. Operation rules are generated on the basis of economic development criteria such as hydropower; municipal; industrial and irrigation demands; flood control and navigation; and environmental criteria such as water quality for fish and wildlife preservation, recreational needs, and downstream how regulation. The fuzzy rule-based model operates on an ''if-then'' principle, where the ''if'' is a vector of fuzzy explanatory variables or premises and ''then,'' of fuzzy consequences. The reservoir storage level, estimated inflows, and demands are used as the premises and release from the reservoir is taken as the consequence. Split sampling of historical data (mean daily time series of flow, lake level, demands, and releases) is used to train and then validate the rules. Different performance indices are calculated and two figures of merit, namely, engineering sustainability and engineering risk are developed for evaluating the rules generated by the model, which appears to be easy to construct, apply, and extend to a complex system of reservoirs.
引用
收藏
页码:262 / 269
页数:8
相关论文
共 50 条
  • [1] Reservoir operation using a dynamic programming fuzzy rule-based approach
    Mousavi, SJ
    Ponnambalam, K
    Karray, F
    WATER RESOURCES MANAGEMENT, 2005, 19 (05) : 655 - 672
  • [2] Fuzzy rule-based model to optimize outflow in single reservoir operation
    Soentoro, Edy Anto
    Pebriana, Nina
    2ND CONFERENCE FOR CIVIL ENGINEERING RESEARCH NETWORKS (CONCERN-2 2018), 2019, 270
  • [3] Stratigraphic rule-based reservoir modeling
    Pyrcz, Michael J.
    Sech, Richard P.
    Covault, Jacob A.
    Willis, Brian J.
    Sylvester, Zoltan
    Sun, Tao
    BULLETIN OF CANADIAN PETROLEUM GEOLOGY, 2015, 63 (04) : 287 - 303
  • [4] Fuzzy Inference System for Robust Rule-Based Reservoir Operation under Nonstationary Inflows
    Yang, Pan
    Ng, Tze Ling
    JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 2017, 143 (04)
  • [5] FUZZY MODELING AND FUZZY RULE-BASED CONTROL OF FMS
    CAPKOVIC, F
    IFIP TRANSACTIONS B-APPLICATIONS IN TECHNOLOGY, 1992, 1 : 281 - 286
  • [6] Fuzzy rule-based model for hydropower reservoirs operation
    Moeini, R.
    Afshar, A.
    Afshar, M. H.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2011, 33 (02) : 171 - 178
  • [7] A fuzzy rule-based modeling of the Sociology of Organized Action
    Sandri, Sandra
    Sibertin-Blanc, Christophe
    ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT, 2007, 163 : 281 - +
  • [8] A fuzzy clustering-based rapid prototyping for fuzzy rule-based modeling
    Delgado, M
    GomezSkarmeta, AF
    Martin, F
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1997, 5 (02) : 223 - 233
  • [9] Granular Fuzzy Rule-Based Modeling With Incomplete Data Representation
    Hu, Xingchen
    Shen, Yinghua
    Pedrycz, Witold
    Li, Yan
    Wu, Guohua
    IEEE TRANSACTIONS ON CYBERNETICS, 2022, 52 (07) : 6420 - 6433
  • [10] Application of fuzzy rule-based modeling technique to regional drought
    Pongracz, R
    Bogardi, I
    Duckstein, L
    JOURNAL OF HYDROLOGY, 1999, 224 (3-4) : 100 - 114