All Outputs (2)

A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation (2014)
Journal Article
Tapoglou, E., Karatzas, G. P., Trichakis, I. C., & Varouchakis, E. A. (2014). A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation. Journal of hydrology, 519(PD), 3193-3203. https://doi.org/10.1016/j.jhydrol.2014.10.040

Artificial Neural Networks (ANNs) and Kriging have both been used for hydraulic head simulation. In this study, the two methodologies were combined in order to simulate the spatial and temporal distribution of hydraulic head in a study area. In order... Read More about A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation.

Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization (2014)
Journal Article
Tapoglou, E., Trichakis, I. C., Dokou, Z., Nikolos, I. K., & Karatzas, G. P. (2014). Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization. Hydrological Sciences Journal, 59(6), 1225-1239. https://doi.org/10.1080/02626667.2013.838005

Artificial neural networks (ANNs) have recently been used to predict the hydraulic head in well locations. In the present work, the particle swarm optimization (PSO) algorithm was used to train a feed-forward multi-layer ANN for the simulation of hyd... Read More about Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization.