Update README.md

README.md

@@ -1,31 +1,31 @@
-# Groundwater-Level-Forecasting-with-Artificial-Neural-Networks-A-Comparison-of-LSTM-CNN-and-NARX
-doi of this repo:  XXXX - will be added  
+# Groundwater Level Forecasting with ANNs: A Comparison of LSTM CNN and NARX
+doi of this repo:  XXXX - will be added
 
-doi of according publication:    
+doi of according publication:
 XXXX - will be added once published
 
 This repository enables you to reproduce the results and apply the groundwater level forecasting mehtodology of:     
 *Wunsch, A., Liesch, T., Broda, S., Groundwater Level Forecasting with Artificial Neural Networks: A Comparison of LSTM, CNN and NARX (submitted)*
 
-Contact: andreas.wunsch@kit.edu    
+Contact: [andreas.wunsch@kit.edu](andreas.wunsch@kit.edu)
 
-ORCIDs of authors:  
-A. Wunsch:  0000-0002-0585-9549   
-T. Liesch:  0000-0001-8648-5333    
-S. Broda:  0000-0001-6858-6368   
+ORCIDs of authors:
+A. Wunsch:  [0000-0002-0585-9549](https://orcid.org/)
+T. Liesch:  [0000-0001-8648-5333](https://orcid.org/)
+S. Broda:  [0000-0001-6858-6368](https://orcid.org/)
 
 For a detailed description please refer to the publication.
 Please adapt all absolute loading/saving and software paths within the scripts to make them running, you need Matlab and Python software for  a successful application.
 
-# Content Overview:
+### Content Overview:
 * /CNN - Python Code
-Verweis auf BeaysOpti Packet welches genutzt wird (im Paper drin?)
-
-
+Contains Python scripts of the models and necessary example files.
 
 * /LSTM - Python Code
+Contains Python scripts of the models and necessary example files.
 
+* /NARX - Matlab Code
+Contains Matlab scripts of the models and necessary example files.
 
-
-
-* /NARX - Matlab Code
+### General remarks
+We use the Python Package [BayesianOptimization](https://github.com/fmfn/BayesianOptimization) by [fmfn](https://github.com/fmfn). To run the Python Code please download and install this package.