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
doaj +1 more source
Thermal error modelling of machine tools based on ANFIS with fuzzy c-means clustering using a thermal imaging camera [PDF]
, 2015 Thermal errors are often quoted as being the largest contributor to CNC machine tool errors, but they can be effectively reduced using error compensation.
Longstaff, Andrew P. +5 more
core +1 more source
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
doaj +1 more source
Applying the possibilistic C-means algorithm in kernel-induced spaces [PDF]
, 2010 In this paper, we study a kernel extension of the classic possibilistic c-means. In the proposed extension, we implicitly map input patterns into a possibly high-dimensional space by means of positive semidefinite kernels. In this new space, we model the
Masulli, F. +5 more
core +1 more source
Clustering as a tool for self-generation of intelligent systems : a survey. [PDF]
, 2010 Fuzzy Rule Based (FRB) and Neuro-fuzzy systems are commonly used as a basis for intelligent systems due to their transparent and simple human interpretable structure.
Angelov, Plamen, Dutta Baruah, Rashmi
core +3 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
SISTEM IDENTIFIKASI KONDISI UDARA MEMANFAATKAN UAV HELIKOPTER BERBASIS FUZZY C- MEANS CLUSTERING [PDF]
, 2011 Kini kita merasakan musim yang sudah tidak jelas, iklim yang berubah-ubah dengan kondisi cuaca yang tidak menentu. Mungkin hal tersebut salah satunya disebabkan telah tercemarnya udara.
Bima Sena Bayu, Bima +2 more
core
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
wiley +1 more source