UNSUPERVISED LEARNING FOR THE IDENTIFICATION OF HOMOGENEOUS FOREST LANDSCAPES
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Date
2024-06
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Abstract
This study focuses on collecting information about Djebel messaad Forest from various
sources and integrating it into a database. The importance of effectively analyzing this data to
achieve specific objectives is noted. The database is considered a crucial source for leveraging
available data, requiring the use of appropriate analytical techniques to extract valuable
insights. The memorandum explores the use of K-Means clustering and hierarchical
algorithms as primary tools for data analysis. The goal of applying clustering algorithms is to
group data into clusters characterized by maximum similarity within plant and flower data in
each cluster, and maximum dissimilarity between different clusters. Through the analysis of
data using these algorithms, we were able to achieve satisfactory results that contribute to a
better understanding of the data and the attainment of specific objectives.
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Keywords
Forest landscape, forest ecosystem, clustering, data mining, data analysis