naspaclust: A hybridisation of spatial fuzzy clustering with nature-inspired optimisation
We present an overview of R package called \texttt{naspaclust}, a tool for spatial fuzzy clustering improvement by hybridising the Fuzzy Geographically Weighted Clustering (FGWC) with nature-inspired optimisation algorithms. There are seven optimisation algorithms in general, namely Artificial Bee Colony, Flower Pollination Algorithm, Gravitational Search Algorithm, Harris-Hawk Optimisation, Intelligent Firefly Algorithm, Particle Swarm Optimisation, and Teaching-Learning Based optimisation. The optimisation algorithms available do not only use the basic algorithms, but also the modified version of several parts such as randomisation terms and updating rules. Furthermore, we also provide ...
| Authors | Bahrul Ilmi Nasution, Rezzy Eko Caraka, Robert Kurniawan |
|---|---|
| Primary category | cs.NE |
| Published | 12 October 2026 |
| Last updated at source | 12 October 2026 |
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