Artificial Neural Network and Differential Evolution methodologies used in single- and multi-objective formulations for the solution of subsurface water management problems

Authors:
Ioannis K. Nikolos;Maria P. Papadopoulou;George P. Karatzas
Affiliations:
Department of Production Engineering and Management, Technical University of Crete, University Campus, Kounoupidiana, 73100, Chania, Greece.;School of Rural and Surveying Engineering, National Technical University of Athens, University Campus, 9 Iroon Polytechneiou, Zografou 15780, Greece.;Department of Environmental Engineering, Technical University of Crete, University Campus, Kounoupidiana 73100, Chania, Greece
Venue:
International Journal of Advanced Intelligence Paradigms
Year:
2010

Citing 5
Cited 0

Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)

Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Using interactive archives in evolutionary multiobjective optimization: A case study for long-term groundwater monitoring design

Environmental Modelling & Software
Groundwater Numerical Modeling and Environmental Design Using Artificial Neural Networks and Differential Evolution

KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II

Quantified Score

Hi-index	0.00

Visualization

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.