2020
DOI: 10.1088/1742-6596/1500/1/012010
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Analysis of a cans waste classification system based on the CMYK color model using different metric distances on the k-means method

Abstract: This study aims to build and analyze a classification system of can waste based on Cyan, Magenta, Yellow, and Black (CMYK) digital image color model by implementing 3 different metric distances on the k-means method; Manhattan, Euclidean, and Minkowski. The classification results of experimental data note that the implementation of Euclidean distance on the k-means clustering method for classifying the cans waste into three can types has the highest accuracy, with a difference of not more than 1% from Minkowsk… Show more

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Cited by 6 publications
(4 citation statements)
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“…The spread of states in clusters was also performed by SPSS software. Each group contained states that have the average of wtotal, wmanag, wtreat variables within a narrow range of values, as in the "k-means cluster" algorithm [45][46][47][48][49].…”
Section: Methodsmentioning
confidence: 99%
“…The spread of states in clusters was also performed by SPSS software. Each group contained states that have the average of wtotal, wmanag, wtreat variables within a narrow range of values, as in the "k-means cluster" algorithm [45][46][47][48][49].…”
Section: Methodsmentioning
confidence: 99%
“…On the other hand, the K-Means technique was not acceptable for this situation because it only yielded less than 70% [16].…”
Section: Related Workmentioning
confidence: 99%
“…Secondly, a cluster analysis was performed to emphasise which countries are more innovative, and the factors that nudge innovation [42][43][44]. Studying the two criteria (patent, invest), one may observe that countries such as Italy (cluster 1), France (cluster 2), and Spain (cluster 6) form clusters by themselves (Table 4).…”
Section: The Second Stage-k Means Cluster Analysismentioning
confidence: 99%