Artificial Neural Network and Differential Evolution methodologies used in single- and multi-objective formulations for the solution of subsurface water management problems. (4th November 2010)

• Record Type: Journal Article
• Authors: Nikolos, Ioannis K.; Papadopoulou, Maria P.; Karatzas, George P.
• Is Part Of: International journal of advanced intelligence paradigms. Volume 2:Number 4(2010)
• Page Start: 365
• Page End: 377
• Publication Date: 2010-11-04
• Subjects: multi-objective optimisation -- subsurface water management -- ANNs -- artificial neural networks -- differential evolution -- groundwater management -- simulation; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

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.