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The Arial data contains date periodically observed with parameters of texture (min, max), flora, and density (min, max). The proposed Arial prediction system cluster and analyze, three input features that is average texture, flora, average density according to number of days to predict Arial for Surveillance applications. The proposed system realizes the k-means clustering algorithm for grouping similar features based on user intended period, further the system analyze using PCA (Principal Component Analysis) on same data.
vudasreenivasarao. 1970. \u201cA Classification of Arial Data Based on Data Mining Clustering Algorithm\u201d. Unknown Journal GJCST Volume 11 (GJCST Volume 11 Issue 22): .
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Total Score: 118
Country: Unknown
Subject: Uncategorized
Authors: Dr.G.Ramaswamy,Dr. Vuda.Sreenivasarao,Dr.P.Ramesh P.V.V.S.Gangadhar (PhD/Dr. count: 3)
View Count (all-time): 145
Total Views (Real + Logic): 20433
Total Downloads (simulated): 10584
Publish Date: 1970 01, Thu
Monthly Totals (Real + Logic):
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The Arial data contains date periodically observed with parameters of texture (min, max), flora, and density (min, max). The proposed Arial prediction system cluster and analyze, three input features that is average texture, flora, average density according to number of days to predict Arial for Surveillance applications. The proposed system realizes the k-means clustering algorithm for grouping similar features based on user intended period, further the system analyze using PCA (Principal Component Analysis) on same data.
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