Results 41 to 50 of about 1,834,948 (246)
Genetic K-means algorithm [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1999 In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both.
Krishna, K, Murty, Narasimha M
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Introduction to Geographic and Spatial Approaches in the History of Archaeology
Bulletin of the History of Archaeology, 2015 Who studies the historiography of archaeology? Who reads the history of the discipline? Recent years have seen growing interest in the history of archaeology as is reflected in works such as Christenson (1989), Trigger (1989; 2006), Chakrabarti (1988 ...
Neha Gupta, Bernard K Means
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2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 The Lloyd-Max algorithm is a classical approach to perform K-means clustering. Unfortunately, its cost becomes prohibitive as the training dataset grows large. We propose a compressive version of K-means (CKM), that estimates cluster centers from a sketch, i.e. from a drastically compressed representation of the training dataset.
Keriven, Nicolas +3 more
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Advanced Approach of Material Region Detections on Fibre-Reinforced Concrete CT-Scans
Advances in Electrical and Electronic Engineering, 2017 Detections of material regions on CT-scans of solids are commonly treated manually by an expert. Although such manual detections have many advantages, some amount of human error is also incorporated. Moreover, expert opinions may vary significantly.
Marek Pecha +4 more
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JOIV: International Journal on Informatics Visualization, 2023 The menu is one of the most fundamental aspects of business continuity in the culinary industry. One of the tools that can be used for menu analysis is menu engineering.
Nina Setiyawati +2 more
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Deep k-Means: Jointly clustering with k-Means and learning representations
Pattern Recognition Letters, 2020 Under consideration at Pattern Recognition ...
Moradi Fard, Maziar +2 more
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Unsupervised K-Means Clustering Algorithm
IEEE Access, 2020 The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the
Kristina P. Sinaga, Miin-Shen Yang
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A parametric k-means algorithm [PDF]
Computational Statistics, 2007 The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution.
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Applied Sciences, 2023 Diversified noise sources pose great challenges in the engineering of an ANC (active noise control) system design. To solve this problem, this paper proposes an ANC method based on VMD (variational mode decomposition) and Ensemble Learning.
Xiaobei Liang +4 more
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Penggunaan N-mers Frequency pada Analisis Barisan DNA
Jambura Journal of Mathematics, 2020 Salah satu metode untuk menganalisis barisan DNA adalah menggunaan N-mers Frequency. N-mers Frequency termasuk metode data mining pada barisan DNA, dimana barisan DNA yang merupakan data string “ACGT” akan diubah menjadi data numerik.
Khoirul Umam, Rahmat Sagara
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