Suchergebnisse - iterative local Gaussian clustering algorithm

An Objective Function-Based Clustering Algorithm with a Closed-Form Solution and Application to Reference Interval Estimation in Laboratory Medicine.

Autoren: Klawonn, Frank Hoffmann, Georg

Quelle: Algorithms. Apr2024, Vol. 17 Issue 4, p143. 13p.

Schlagwörter: *CLINICAL pathology, *GAUSSIAN mixture models, *K-means clustering, *ALGORITHMS

Diversity-induced fuzzy clustering with Laplacian regularization.

Autoren: Gao, Yunlong Wu, Qinting Xu, Zhenghong et al.

Quelle: Information Sciences. Oct2025, Vol. 715, pN.PAG-N.PAG. 1p.

Schlagwörter: *GAUSSIAN distribution, *DATA structures, CLUSTERING algorithms, FUZZY algorithms, EUCLIDEAN distance

Non-iterative border-peeling clustering algorithm based on swap strategy.

Autoren: Tu, Hui Ding, Shifei Xu, Xiao et al.

Quelle: Information Sciences. Jan2024, Vol. 654, pN.PAG-N.PAG. 1p.

Schlagwörter: *ALGORITHMS, DOCUMENT clustering, K-nearest neighbor classification, SPECIFIC gravity, BORDERLANDS

An Adaptive Spectral Clustering Algorithm Based on the Importance of Shared Nearest Neighbors.

Autoren: Xiaoqi He Sheng Zhang Yangguang Liu

Quelle: Algorithms. 2015, Vol. 8 Issue 2, p177-189. 13p.

Schlagwörter: *ALGORITHMS, *KERNEL functions, *GAUSSIAN function, *MATRICES (Mathematics), *ITERATIVE methods (Mathematics)

An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions.

Autoren: Zhang, Jiangjiang Zeng, Lingzao Lin, Guang et al.

Quelle: Water Resources Research; Mar2018, Vol. 54 Issue 3, p1716-1733, 18p

Schlagwörter: HYDROLOGIC models, COMPUTATIONAL hydrology software, ALGORITHMS

Research on a Segmentation Algorithm for the Tujia Brocade Images Based on Unsupervised Gaussian Mixture Clustering.

Autoren: He, Shuqi

Quelle: Frontiers in Neurorobotics; 9/3/2021, Vol. 15, p1-15, 15p

Schlagwörter: GAUSSIAN mixture models, DEEP learning, IMAGE segmentation, ALGORITHMS, RANDOM fields, CULTURAL property

An enhanced microstate clustering algorithm based on canopy, K-means, and genetic simulated annealing.

Autoren: Liang, Jingting Yin, Xiangguo Lin, Mingxing

Quelle: Biomedical Physics & Engineering Express; Jul2025, Vol. 11 Issue 4, p1-14, 14p

Research on Arch Dam Deformation Safety Early Warning Method Based on Effect Separation of Regional Environmental Variables and Knowledge-Driven Approach.

Autoren: Wang, Jianxue Tong, Fei Gao, Zhiwei et al.

Quelle: Water (20734441); Nov2025, Vol. 17 Issue 22, p3217, 25p

Schlagwörter: ARCH dams, PRINCIPAL components analysis, STRUCTURAL health monitoring, FAULT diagnosis, CLUSTERING algorithms, SAFETY

A Task-Related EEG Microstate Clustering Algorithm Based on Spatial Patterns, Riemannian Distance, and a Deep Autoencoder.

Autoren: Pan, Shihao Shen, Tongyuan Lian, Yongxiang et al.

Quelle: Brain Sciences (2076-3425); Jan2025, Vol. 15 Issue 1, p27, 24p

Schlagwörter: CLUSTERING algorithms, AUTOENCODERS, COGNITIVE neuroscience, COGNITIVE structures, ELECTROENCEPHALOGRAPHY

BRAIN TUMOR SEGMENTATION BASED ON SUPERPIXELS AND HYBRID CLUSTERING WITH FAST GUIDED FILTER.

Autoren: ZHANG, CHONG SHEN, XUANJING CHEN, HAIPENG

Quelle: Journal of Mechanics in Medicine & Biology; Aug2020, Vol. 20 Issue 6, pN.PAG-N.PAG, 18p

Schlagwörter: BRAIN tumors, BRAIN cancer diagnosis, ALGORITHMS, ADAPTIVE filters, MAGNETIC resonance, IMAGE segmentation

Image clustering algorithm using superpixel segmentation and non-symmetric Gaussian–Cauchy mixture model.

Autoren: Ji, Sifan Zhu, Hongqing Wang, Pengyu et al.

Quelle: IET Image Processing (Wiley-Blackwell); 2020, Vol. 14 Issue 16, p4132-4143, 12p

Schlagwörter: GAUSSIAN mixture models, GAUSSIAN distribution, ALGORITHMS, PIXELS, MIXTURES

Fuzzy C‐means clustering algorithm based on superpixel merging and multi‐feature adaptive fusion measurement.

Autoren: Zeyu, Xie Xiao, Luo Defang, Zhao et al.

Quelle: IET Image Processing (Wiley-Blackwell); 1/10/2024, Vol. 18 Issue 1, p140-153, 14p

Schlagwörter: PIXELS, IMAGE segmentation, ALGORITHMS, FUZZY algorithms, BRAIN tumors, INFORMATION measurement, INFORMATION resources

Semi-Supervised Soft Computing for Ammonia Nitrogen Using a Self-Constructing Fuzzy Neural Network with an Active Learning Mechanism.

Autoren: Zhou, Hongbiao Huang, Yang Yang, Dan et al.

Quelle: Water (20734441); Oct2024, Vol. 16 Issue 20, p3001, 26p

Schlagwörter: FUZZY neural networks, STANDARD deviations, SOFT computing, K-means clustering, WATER quality

Application of Artificial Intelligence Technologies as an Intervention for Promoting Healthy Eating and Nutrition in Older Adults: A Systematic Literature Review.

Autoren: Kalu, Kingsley Ataguba, Grace Onifade, Oyepeju et al.

Quelle: Nutrients. Oct2025, Vol. 17 Issue 20, p3223. 33p.

Hierarchical modeling of risk factors with and without prior information—the process of regression model evaluation for an example of respiratory diseases in piglet production from daily practice data.

Autoren: Tug, Timur Mers, Fiona Schäkel, Franziska et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-16. 16p.

Fast and Effective Active Clustering Ensemble Based on Density Peak.

Autoren: Shi, Yifan Yu, Zhiwen Cao, Wenming et al.

Quelle: IEEE Transactions on Neural Networks & Learning Systems; Aug2021, Vol. 32 Issue 8, p3593-3607, 15p

Schlagwörter: DENSITY, REDUNDANCY in engineering, ALGORITHMS, TOY industry

A shape‐based clustering algorithm and its application to load data.

Autoren: Li, Naiwen Wu, Xian Dong, Jianjun et al.

Quelle: Cognitive Computation & Systems; Jun2023, Vol. 5 Issue 2, p109-117, 9p

Schlagwörter: TIME series analysis, MARKET segmentation, CLUSTER analysis (Statistics), CONSUMERS, ENERGY industries

Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models.

Autoren: Campbell, Trevor Kulis, Brian How, Jonathan

Quelle: IEEE Transactions on Pattern Analysis & Machine Intelligence; Jun2019, Vol. 41 Issue 6, p1338-1352, 15p

Schlagwörter: ALGORITHMS, MARKOV processes, HEURISTIC algorithms, BAYESIAN analysis, METHODOLOGY

Incremental Local Distribution-Based Clustering Using Bayesian Adaptive Resonance Theory.

Autoren: Wang, Ling Zhu, Hui Meng, Jianyao et al.

Quelle: IEEE Transactions on Neural Networks & Learning Systems; Nov2019, Vol. 30 Issue 11, p3496-3504, 9p

Schlagwörter: RESONANCE, INCREMENTAL motion control, COVARIANCE matrices

A Robust Fuzzy Local Information C-Means Clustering Algorithm.

Autoren: Krinidis, Stelios Chatzis, Vassilios

Quelle: IEEE Transactions on Image Processing; May2010, Vol. 19 Issue 5, p1328-1337, 10p, 1 Color Photograph, 5 Black and White Photographs, 4 Charts, 1 Graph

Schlagwörter: IMAGE processing, ALGORITHMS, FUZZY algorithms, IMAGE reconstruction, ROBUST control