The code and datasets presented here are part of deliverable D3.1 Selection of the Smart Model Types Suitable for Application to Groundwater Systems. Two applications (Case1 and 2 of deliverable D3.1) are presented. Specifically, the files consist of: input and output datasets for training the neural networks and the surrogate model codes.This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart model types suitable for application to groundwater systems "Innovative and Sustainable Groundwater Management in the Mediterranean" Grant Agreement Number 1923 project
The overall objective of the InTheMED project is to implement innovative and sustainable management ...
The overall objective of the InTheMED project is to implement innovative and sustainable management ...
Abstract. An attempt is made to integrate groundwater models within a decision support system (DSS) ...
The code and datasets presented here are part of deliverable D3.1 Selection of the Smart Model Types...
This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart mod...
This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart mod...
This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart mod...
This deliverable summarizes the activities carried out in Task 3.2: “Training and Validation of the ...
In recent years, drought and demand growth in most parts of the county have caused a dramatic increa...
The report on the "Numeric Simulation Model Including Model Input Files" is the milestone number D4....
Four algorithms are outlined, each of which has interesting features for predicting contaminant leve...
Groundwater is one of the most important freshwater resources, especially in arid and semi-arid regi...
Summarization: A Differential Evolution (DE) algorithm is combined with an Artificial Neural Network...
As a result of an ever increasing number of reports on groundwater contamination, people have come t...
Groundwater is a vital source of freshwater, supporting the livelihood of over two billion people wo...
The overall objective of the InTheMED project is to implement innovative and sustainable management ...
The overall objective of the InTheMED project is to implement innovative and sustainable management ...
Abstract. An attempt is made to integrate groundwater models within a decision support system (DSS) ...
The code and datasets presented here are part of deliverable D3.1 Selection of the Smart Model Types...
This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart mod...
This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart mod...
This document represents the evidence of compliance with Deliverable 3.1: Selection of the smart mod...
This deliverable summarizes the activities carried out in Task 3.2: “Training and Validation of the ...
In recent years, drought and demand growth in most parts of the county have caused a dramatic increa...
The report on the "Numeric Simulation Model Including Model Input Files" is the milestone number D4....
Four algorithms are outlined, each of which has interesting features for predicting contaminant leve...
Groundwater is one of the most important freshwater resources, especially in arid and semi-arid regi...
Summarization: A Differential Evolution (DE) algorithm is combined with an Artificial Neural Network...
As a result of an ever increasing number of reports on groundwater contamination, people have come t...
Groundwater is a vital source of freshwater, supporting the livelihood of over two billion people wo...
The overall objective of the InTheMED project is to implement innovative and sustainable management ...
The overall objective of the InTheMED project is to implement innovative and sustainable management ...
Abstract. An attempt is made to integrate groundwater models within a decision support system (DSS) ...