PENERAPAN ALGORITMA GLOWWORM SWARM OPTIMIZATION PADA MODEL GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN KERNEL ADAPTIF
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Authors:
I GEDE HARDI KARMANA, LUH PUTU IDA HARINI, KETUT JAYANEGARA, I PUTU EKA NILA KENCANA
Abstract:
“This study aimed to apply glowworm swarm optimization (GSO) algorithm as an alternate way to obtain optimal bandwidth in geographically weighted regression (GWR) model with adaptive kernel function. The result showed that GSO was able to obtain optimal bandwidth with lower cross validation (CV) value than the traditional way that was using k-nearest neighbor (KNN) algorithm. Unfortunately, the running time of GSO was far slower than KNN was.”
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https://jurnal.harianregional.com/mtk/full-57294
Published
2020-01-31
How To Cite
KARMANA, I GEDE HARDI et al. PENERAPAN ALGORITMA GLOWWORM SWARM OPTIMIZATION PADA MODEL GEOGRAPHICALLY WEIGHTED REGRESSION DENGAN KERNEL ADAPTIF.E-Jurnal Matematika, [S.l.], v. 9, n. 1, p. 79-84, jan. 2020. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-57294. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/MTK.2020.v09.i01.p282.
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Issue
Vol 9 No 1 (2020)
Section
Articles
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This work is licensed under a Creative Commons Attribution 4.0 International License
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