Multidimensional data mining using a K-mean algorithm based on the forest management inventory of Fujian Province, China

Yanrong Guo, Baoguo Wu, Yang Liu

Abstract


To determine relationships between stand volume and site factors in the absence of information about stand age and density, a classification pattern was established using a clustering analysis algorithm and applied to China fir in Fujian Province. The results showed that slope position, elevation, elevation and humus depth were important factors affecting the stand volumes of young/immature forests, near-mature forests, and mature/overmature forests, respectively. The K-mean algorithm could be used to evaluate the influences of site factors on stand volume under different stand age groups and density conditions.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3570


Keywords


Data mining; K-means algorithm; Site factor; Forest management inventory

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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