@incollection{cavalloOptimalFuzzyManagement2008,
  title = {Optimal Fuzzy Management of Reservoir Based on Genetic Algorithm},
  booktitle = {Foundations of {{Generic Optimization}}},
  author = {Cavallo, Alberto and Nardo, Armando},
  editor = {Lowen, Robert and Verschoren, Alain},
  date = {2008},
  volume = {24},
  pages = {139--159},
  publisher = {{Springer Netherlands}},
  doi = {10.1007/978-1-4020-6668-9\\_2},
  url = {https://doi.org/10.1007/978-1-4020-6668-9_2},
  abstract = {This chapter deals with water resource management problems faced from an Automatic Control point of view. The motivation for the study is the need for an automated management policy for an artificial reservoir (dam). A hybrid model of the reservoir is considered and implemented in Stateflow/Simulink, and a fuzzy decision mechanism is implemented in order to produce different water release strategies. A new cost functional is proposed, able to weight user's desiderata (in terms of water demand) with water waste (in terms of water spills). The parameters of the fuzzy system are optimized by employing Genetic Algorithms, which have proved very effective due to the strong nonlinearity of the problem. Modi- fied AR and ARMAX models of the inflow are identified and Montecarlo simulations are used to test the effectiveness of the proposed strategy in different operating scenarios.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-11868171,control-problem,fuzzy,genetic-algorithms,monte-carlo,reservoir-management,water-resources},
  series = {Mathematical {{Modelling}}: {{Theory}} and {{Applications}}}
}

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