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Artificial neural network and differential evolution methodologies used in single – and multi – objective formulations for the solution of subsurface water management problems

Nikolos Ioannis, Papadopoulou Maria P., Karatzas Giorgos

Πλήρης Εγγραφή

URI: http://purl.tuc.gr/dl/dias/A5CB2E20-6954-46D1-A659-D0EABDFF4BD9
Έτος 2010
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά Ι.K. Nikolos , M.P. Papadopoulou, and G.P. Karatzas, "Artificial neural network and differential evolution methodologies used in single – and multi – objective formulations for the solution of subsurface water management problems," International Journal of Advanced Intelligence Paradigms, vol. 2, no.4, pp. 365 - 377, 2010. doi: 10.1504/IJAIP.2010.036401 https://doi.org/10.1504/IJAIP.2010.036401
Εμφανίζεται στις Συλλογές
Δημοσιεύσεις σε Περιοδικά στην Κοινότητα Σχολή Χημικών Μηχανικών και Μηχανικών Περιβάλλοντος

Περίληψη

A single-objective Differential Evolution (DE) algorithm is combined with an Artificial Neural Network (ANN) to examine different operational strategies to cover the water demand in the Northern part of Rhodes Island, Greece. Successive calls to the simulator are used to provide the training data to the ANN, which is used as an approximation model to the simulator. Additionally, a multi-objective DE algorithm is combined with the pre-trained ANN to solve the same problem; the environmental constraints are realised through the definition of a second objective function, whereas the first objective function is the total pumping of the supply wells.

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