Naghmeh Pakgohar

• Doctor of Philosophy of forestry (Quantitative Ecology)
• Research Associate at Northern Alberta Institute of Technology

Aims Different clustering methods often classify the same data set differently. Selecting the “best” clustering solution from alternatives is possible with cluster validation indices. Because of the large variety of cluster validation indices (CVIs), choosing the most suitable index concerning the data set and clustering algorithms is challenging....

Aim s Ecological theories predict that assembly processes are driven by two deterministic forces: environmental filtering and limiting similarity. Their relative importance under different environmental conditions is still not completely obvious. Therefore, in this paper the predictions of the stress–dominance hypothesis (SDH) are tested in several...

Different clustering methods often classify the same dataset differently. Selecting the 'best' clustering solution out of a multitude of alternatives is possible with cluster validation indices. The behavior of validity indices changes with the structure of the sample and the properties of the clustering algorithm. Unique properties of each index c...

Questions Which clustering algorithms are most effective according to different cluster validity evaluators? Which distance or dissimilarity measure is most suitable for clustering algorithms? Location Hyrcanian forest, Iran (Asia), Virginia region forest, United States (North America), Beech forests, Ukraine (Europe) Methods We tested twenty‐fiv...

In this study, two inventory methods, including use of plots with 300 m² fixed-area and Relascope with variable-area plots were compared to evaluate biodiversity, quantitative and qualitative characteristics of Arasbaran forest stands in the North West of Iran. For this purpose, 58 sample plots were specified using 100 m×100 m regular randomized gr...