Results 21 to 30 of about 15,044 (262)
Exploring Fuzzy Local Spatial Information Algorithms for Remote Sensing Image Classification
Remote Sensing, 2021 Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images.
Anjali Madhu, Anil Kumar, Peng Jia
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AN APPROACH TO REMOVE THE EFFECT OF RANDOM INITIALIZATION FROM FUZZY C-MEANS CLUSTERING TECHNIQUE [PDF]
Journal of Process Management and New Technologies, 2014 Out of the different available fuzzy clustering techniques Bezdek’s Fuzzy C-Means clustering technique is among the most popular ones. Due to the random initialization of the membership values the performance of Fuzzy C-Means clustering technique ...
Samarjit Das, Hemanta K. Baruah
doaj
KC-Means: A Fast Fuzzy Clustering
Advances in Fuzzy Systems, 2018 A novel hybrid clustering method, named KC-Means clustering, is proposed for improving upon the clustering time of the Fuzzy C-Means algorithm. The proposed method combines K-Means and Fuzzy C-Means algorithms into two stages.
Israa Abdzaid Atiyah +2 more
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Combining Fuzzy C-Means Clustering with Fuzzy Rough Feature Selection
Applied Sciences, 2019 With the rapid development of the network, data fusion becomes an important research hotspot. Large amounts of data need to be preprocessed in data fusion; in practice, the features of datasets can be filtered to reduce the amount of data.
Ruonan Zhao, Lize Gu, Xiaoning Zhu
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IMPLEMENTASI FUZZY C-MEANS CLUSTERING DALAM PENENTUAN BEASISWA
Barekeng, 2017 Logika fuzzy merupakan salah satu komponen pembentuk Soft Computing, yaitu suatu cara yang tepat untuk memetakan suatu ruang input ke dalam suatu ruang output.
Dorteus L. Rahakbauw +2 more
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Electrical fuzzy C-means: A new heuristic fuzzy clustering algorithm
Cogent Engineering, 2016 Many heuristic and meta-heuristic algorithms have been successfully applied in the literature to solve the clustering problems. The algorithms have been created for partitioning and classifying a set of data because of two main purposes: at first, for ...
Esmaeil Mehdizadeh, Amir Golabzaei
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Spatial biology in cancer epigenetics
Molecular Oncology, EarlyView.Spatial epigenomics combines molecular profiling with tissue architecture to reveal how gene regulation is organized within intact tissues. In cancer, these technologies uncover the mechanisms driving tumor heterogeneity and microenvironmental interactions, opening new opportunities for biomarker discovery and precision medicine.
Eva Crespo‐García, Manel Esteller
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Clustering Analysis for the Pareto Optimal Front in Multi-Objective Optimization
Computation, 2022 Bio-inspired algorithms are a suitable alternative for solving multi-objective optimization problems. Among different proposals, a widely used approach is based on the Pareto front.
Lilian Astrid Bejarano +2 more
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Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies
FEBS Open Bio, EarlyView.We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli +8 more
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Protocol for quantifying miRNA trafficking across the endosomal membrane
FEBS Open Bio, EarlyView.An in vitro protocol measures miRNA uptake into endosomes isolated from mammalian cell extracts, which are free of subcellular contaminants. Performed at 37 °C in the presence of ATP, it ensures the import of single‐stranded miRNA into the endosomal lumen.
Syamantak Ghosh +2 more
wiley +1 more source