4 dépôts
Frameworks and tools for spatial machine learning and data analysis.
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This project is a neural network route optimizer and unsupervised learning tool designed to solve the traveling salesman problem. It functions as a self-organizing map solver that calculates near-optimal paths through a set of coordinates to determine the shortest possible tour. The system utilizes a Kohonen map implementation to organize high-dimensional data into a lower-dimensional representation. It employs competitive learning and topology preservation to approximate solutions for combinatorial optimization problems. The solver covers route optimization analysis and heuristic pathfindin
Solves the Traveling Salesman Problem using Self-Organizing Maps.
Transform geospatial relations into graphs for Graph Neural Networks and network analysis
Converts geospatial datasets into graphs for GeoAI.
Spatial Representations for Artificial Intelligence - a Python library toolkit for geospatial machine learning focused on creating embeddings for downstream tasks
Provides tools for geospatial machine learning and wrangling.
A toolbox for processing earth observation data with Python.
Provides an Earth observation framework for machine learning.