Suchergebnisse - Clustering— Algorithms General Terms Algorithms

Clustering algorithms: A comparative approach von Rodriguez, Mayra Z., Comin, Cesar H., Casanova, Dalcimar, Bruno, Odemir M., Amancio, Diego R., Costa, Luciano da F., Rodrigues, Francisco A.

“… Many real-world systems can be studied in terms of pattern recognition tasks, so that proper use (and understanding …”
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Comprehensive survey on hierarchical clustering algorithms and the recent developments von Ran, Xingcheng, Xi, Yue, Lu, Yonggang, Wang, Xiangwen, Lu, Zhenyu

“… Data clustering is a commonly used data processing technique in many fields, which divides objects into different clusters in terms of some similarity measure between data points …”
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Structural k-means (S k-means) and clustering uncertainty evaluation framework (CUEF) for mining climate data von Doan, Quang-Van, Amagasa, Toshiyuki, Pham, Thanh-Ha, Sato, Takuto, Chen, Fei, Kusaka, Hiroyuki

“… One of the most popular data clustering/mining techniques is k-means, and it has been used to detect hidden patterns in climate systems …”
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Sparse Subspace Clustering: Algorithm, Theory, and Applications von Elhamifar, E., Vidal, R.

“… In this paper, we propose and study an algorithm, called sparse subspace clustering, to cluster data points that lie in a union of low-dimensional subspaces …”
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Data mining algorithms for bridge health monitoring: Kohonen clustering and LSTM prediction approaches von Guo, Aiping, Jiang, Ajuan, Lin, Jie, Li, Xiaoxiao

“… This paper utilizes two algorithms to deal with the massive data, namely Kohonen neural network and long short-term memory (LSTM) neural network …”
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Clustering algorithms based on correlation coefficients for probabilistic linguistic term sets von Lin, Mingwei, Wang, Huibing, Xu, Zeshui, Yao, Zhiqiang, Huang, Jinli

“… Therefore, some correlation coefficient formulas are put forward to measure the relationship between two PLTSs and then they are utilized to develop two novel clustering algorithms to group PLTSs in this paper …”
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General Type-2 Fuzzy C-Means Algorithm for Uncertain Fuzzy Clustering von Linda, O., Manic, M.

“… The focus of this paper is the management of uncertainty associated with parameters of fuzzy clustering algorithms. Type-2 fuzzy sets (T2 FSs …”
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Co-Clustering: Models, Algorithms and Applications von Govaert, Gérard, Nadif, Mohamed

“… -established, as well as more recent methods of co-clustering …”
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An image fusion algorithm based on image clustering theory: An image fusion algorithm based on image clustering theory von Zhao, Liangjun, Wang, Yinqing, Hu, Yueming, Dai, Hui, Xi, Yubin, Ning, Feng, He, Zhongliang, Liang, Gang, Zhang, Yuanyang

“… This article proposes a multi-scale image fusion method based on robust self-sparse fuzzy clustering …”
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Modeling and short-term prediction of HVAC system with a clustering algorithm von Tang, Fan, Kusiak, Andrew, Wei, Xiupeng

“… •Modeling and short-term prediction of HVAC system.•MLP ensemble performs best among five data-mining algorithms …”
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MeShClust v3.0: high-quality clustering of DNA sequences using the mean shift algorithm and alignment-free identity scores von Girgis, Hani Z.

“… ; however, there is a big room for improvement in terms of cluster quality. Motivated by this opportunity for improving cluster quality, we applied the mean shift algorithm in MeShClust v1.0 …”
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Automatic modulation classification method using fixed K-means algorithm for feature clustering processing von Yuan, Li, Chen, Yang

“… Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder …”
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K-Means-Based Nature-Inspired Metaheuristic Algorithms for Automatic Data Clustering Problems: Recent Advances and Future Directions von Ikotun, Abiodun M., Almutari, Mubarak S., Ezugwu, Absalom E.

“… K-means clustering algorithm is a partitional clustering algorithm that has been used widely in many applications for traditional clustering due to its simplicity and low computational complexity …”
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Sparrow search algorithm-driven clustering analysis of rock mass discontinuity sets von Wu, Wenxuan, Feng, Wenkai, Yi, Xiaoyu, Zhao, Jiachen, Zhou, Yongjian

“… In this paper, a novel clustering approach based on the sparrow search algorithm (SSA) is introduced to overcome these limitations …”
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A Novel Hybrid Technique of Integrating Gradient-Boosted Machine and Clustering Algorithms for Lithology Classification von Asante-Okyere, Solomon, Shen, Chuanbo, Ziggah, Yao Yevenyo, Rulegeya, Mercy Moses, Zhu, Xiangfeng

“… To the best of our knowledge, a hybrid lithology classification model that integrates clustering results of well log data has not been …”
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Detecting and analysing the topology of the cosmic web with spatial clustering algorithms I: methods von Kelesis, Dimitrios, Basilakos, Spyros, Papadopoulou Lesta, Vicky, Fotakis, Dimitris, Efstathiou, Andreas

“… ABSTRACT In this paper, we explore the use of spatial clustering algorithms as a new computational approach for modelling the cosmic web …”
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An intelligent cluster optimization algorithm based on Whale Optimization Algorithm for VANETs (WOACNET) von Husnain, Ghassan, Anwar, Shahzad

“… Whale Optimization Algorithm for Clustering in Vehicular Ad hoc Networks (WOACNET) was introduced to select an optimum cluster head (CH …”
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Analyzing fulminant myocarditis research trends and characteristics using the follower-leading clustering algorithm (FLCA): A bibliometric study von Yen, Pei-Chun, Chou, Willy, Chien, Tsair-Wei, Jen, Tung-Hui

“… Limited research has been conducted on FM characteristics using cluster analysis. This study introduces the following-leading clustering algorithm …”
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Lotus effect optimization algorithm (LEA): a lotus nature-inspired algorithm for engineering design optimization von Dalirinia, Elham, Jalali, Mehrdad, Yaghoobi, Mahdi, Tabatabaee, Hamid

“… Here we introduce a new evolutionary algorithm called the Lotus Effect Algorithm, which combines efficient operators from the dragonfly algorithm, such as the movement of dragonflies in flower …”
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MapReduce algorithms for robust center-based clustering in doubling metrics von Dandolo, Enrico, Mazzetto, Alessio, Pietracaprina, Andrea, Pucci, Geppino

“… ) clustering problems. A more general variant, introduced to deal with noisy pointsets, features a further parameter z and allows up to z points of P (outliers …”
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