Results 21 to 30 of about 15,644,966 (296)
CLUSTERING OF EARTHQUAKE RISK IN INDONESIA USING K-MEDOIDS AND K-MEANS ALGORITHMS
Media Statistika, 2020 Earthquake is the shaking of the earth's surface due to the shift in the earth's plates. This disaster often happens in Indonesia due to the location of the country on the three largest plates in the world and nine small others which meet at an area to ...
Isna Hidayatur Rifa +2 more
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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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Relational Algorithms for k-means Clustering
CoRR, 2020 This paper gives a k-means approximation algorithm that is efficient in the relational algorithms model. This is an algorithm that operates directly on a relational database without performing a join to convert it to a matrix whose rows represent the data points.
Moseley, Benjamin +3 more
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Application of K-Means Clustering Algorithm for Determination of Fire-Prone Areas Utilizing Hotspots in West Kalimantan Province [PDF]
, 2020 Forest and land fires are disasters that often occur in Indonesia. In 2007, 2012 and 2015 forest fires that occurred in Sumatra and Kalimantan attracted global attention because they brought smog pollution to neighboring countries.
Sutoyo, Edi, Khairani, Nabila Amalia
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K-Means Algorithm Analysis for Election Cluster Prediction
JOIV: International Journal on Informatics Visualization, 2023 The general election is a democratic process that is carried out in every country whose system of government is presidential, including Indonesia, which conducts it every five years.
Sri Ngudi Wahyuni +2 more
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K-means** - a fast and efficient K-means algorithms
International Journal of Intelligent Information and Database Systems, 2018 K-means often converges to a local optimum. In improved versions of K-means, k-means++ is well-known for achieving a rather optimum solution with its cluster initialisation strategy and high computational efficiency. Incremental K-means is recognised for its converging to the empirically global optimum but having a high complexity due to its stepping ...
Cuong Duc Nguyen, Trong Hai Duong
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A Modified K-means Algorithms - Bi-Level K-Means Algorithm [PDF]
Advances in Intelligent Systems Research, 2014 In this paper, a modified K-means algorithm is proposed to categorize a set of data into smaller clusters. K- means algorithm is a simple and easy clustering method which can efficiently separate a huge number of continuous numerical data with high-dimensions. Moreover, the data in each cluster are similar to one another.
Chia -Yi Chuang +4 more
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Spherical k-Means Clustering [PDF]
, 2012 Clustering text documents is a fundamental task in modern data analysis, requiring approaches which perform well both in terms of solution quality and computational efficiency.
Kurt Hornik +7 more
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Optimization algorithm of K-means fingerprint location
Dianzi Jishu Yingyong, 2018 K-means fingerprint localization can reduce the complexity of localization, and improving the real-time of location has become a hot-spot of current localization algorithm.
Yu Chengbo, Li Caihong, Zeng Liang
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K-Means Algorithm Implementation for Project Health Clustering
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2023 Indonesia has several companies that are involved in the telecommunications sector. Various projects run in parallel to support the success of telecommunications companies. The potential of a project can increase company revenue and productivity. On the
Ajeng Arifa Chantika Rindu +2 more
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