Results 51 to 60 of about 15,644,966 (296)
Illiteracy Classification Using K Means-Naïve Bayes Algorithm
JOIV: International Journal on Informatics Visualization, 2018 Illiteracy is an inability to recognize characters, both in order to read and write. It is a significant problem for countries all around the world including Indonesia.
Muhammad Firman Aji Saputra +2 more
doaj +1 more source
K-Means Algorithm to Identify the Elderly Psychological Stress Analysis Algorithm
Advances in Multimedia, 2022 In order to study the psychological anxiety of the elderly, a psychological stress recognition algorithm based on ECG signal acquisition and heart rate variability was proposed based on the K-means algorithm. By collecting ECG signals of the elderly, HRV
Yan Gao
doaj +1 more source
Image segmentation based on adaptive K-means algorithm
EURASIP Journal on Image and Video Processing, 2018 Image segmentation is an important preprocessing operation in image recognition and computer vision. This paper proposes an adaptive K-means image segmentation method, which generates accurate segmentation results with simple operation and avoids the ...
Xin Zheng +4 more
doaj +1 more source
Making Roasted Mutton Colourimetric Card Based on Machine Vision Technology
Shipin gongye ke-ji, 2022 In order to establish a standardized method that can quickly and nondestructively identify the color changes in the process of mutton roasting, this study combined three algorithms (mean value algorithm, K-means algorithm and K-means+image noise ...
Bo WANG +3 more
doaj +1 more source
The global Minmax k-means algorithm. [PDF]
Springerplus, 2016 The global k-means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k-means to minimize the sum of the intra-cluster variances.
Wang X, Bai Y.
europepmc +4 more sources
Clustering dichotomously scored items through functional k-means algorithm
, 2016 In the educational field, it is common to analyze the probability of a correct response to a test item as a continuous function of the item parameters and the subject ability. This relation is given by the item response function.
Di Battista, Tonio; Dipartimento di Metodi Quantitativi e Teoria Economica, Università "G. d'Annunzio" Chieti-Pescara +3 more
core +1 more source
Identifying Patterns of Hospitalizations Among Childhood Cancer Survivors: A Population‐Based Study
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Childhood cancer survivors (CCSs) experience more hospitalizations than the general population. We aimed to identify distinct hospitalization patterns among Queensland CCSs and the associated characteristics. Methods Cases (aged ≤14 years) diagnosed between 1995 and 2019 while residents of Queensland were identified through the ...
Hai Pham +7 more
wiley +1 more source
An efficient approach based on differential evolution algorithm for data clustering [PDF]
Decision Science Letters, 2014 Clustering plays an essential role for data analysis and it has been widely used in different fields like data mining, machine learning and pattern recognition.
Maryam Hosseini +2 more
doaj +1 more source
Applied Sciences, 2022 Metaheuristic algorithms have been hybridized with the standard K-means to address the latter’s challenges in finding a solution to automatic clustering problems.
Abiodun M. Ikotun, Absalom E. Ezugwu
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An optimized initialization center K-means clustering algorithm based on density
, 2015 Traditional K-means algorithm's clustering effect is affected by the initial cluster center points. To solve this problem, a method is proposed to optimize the K-means initial center points.
Xiaofeng Zhou +5 more
core +1 more source