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The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining.
To run the toolkit, simply download and execute (double-click) the jar-file.
Please cite:
- Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775.
Other related publications:
- Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. Journal of Geographical Systems, 18(1), 1-15.
- Hagenauer, J., & Helbich, M. (2013). Contextual neural gas for spatial clustering and analysis. International Journal of Geographical Information Science, 27(2), 251-266.
Features
- Implements Self-Organizing Map and Neural Gas algorithms
- Supports different approaches for considering spatial dependence
- Provides linkage between networks and geographical data
- Implements powerful clustering algorithms for structuring the networks
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