Search
Search Results
-
Clustering for Bivariate Functional Data
In this paper, we consider the clustering of bivariate functional data where each random surface consists of a set of curves recorded repeatedly for...
-
Statistical Technique in Clustering Problems
AbstractThe problem of evaluating and improving the quality of clustering multispectral data is considered. A method for calculating the distance...
-
A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering
We develop a distributed Block Chebyshev-Davidson algorithm to solve large-scale leading eigenvalue problems for spectral analysis in spectral...
-
Similarity Heuristics for Clustering Wells Based on Logging-Data
AbstractAccurate clustering of oil wells is important for lithological studies and hydrocarbon production processes. Traditional methods for solving...
-
Map** of Fish Consumption in Indonesia Based on Average Linkage Clustering Methods
This study aimed to conduct grou** the level of fish consumption of 34 provinces in Indonesia and then map** it. National Socio-economic Survey...
-
k-Means Clustering in EEG (Brain Waves) Timeseries
Clustering is a process of assigning data points into groups (clusters). The goal is to assign “similar” points to the same cluster, while...
-
Experimental Study of Semi-Supervised Graph 2-Clustering Problem
Based on results of experiments, we analyze the efficiency of some exact and approximation algorithms for a semi-supervised graph 2-clustering...
-
Clustering Models
It is generally accepted that the term “clusterization” (bunch, bundle) was offered by the mathematician R. Trion. Subsequently, a number of terms...
-
Global optimization for cardinality-constrained minimum sum-of-squares clustering via semidefinite programming
The minimum sum-of-squares clustering (MSSC), or k-means type clustering, has been recently extended to exploit prior knowledge on the cardinality of...
-
A Modified Mixture Model-Based Clustering Algorithm for Resolving the Problem of Mixed Pixels Available in Satellite Imagery
AbstractIn this study we present the model-based clustering in order to overcome the problem of mixed pixels for satellite imagery. The mixed pixel...
-
Model-based adaptive locomotion and clustering control of microparticles through ultrasonic topological charge modulation
We present a novel motion control technique for microrobot clusters to exploit the characteristics of the ultrasonic field. The method comprises two...
-
Integer Programming Based Algorithms for Overlap** Correlation Clustering
Clustering is a fundamental problem in data science with diverse applications in biology. The problem has many combinatorial and statistical...
-
Short-term load forecasting using time series clustering
Short-term load forecasting plays a major role in energy planning. Its accuracy has a direct impact on the way power systems are operated and...
-
Koopman-Based Spectral Clustering of Directed and Time-Evolving Graphs
AbstractWhile spectral clustering algorithms for undirected graphs are well established and have been successfully applied to unsupervised machine...
-
Optimizing Parallelization Strategies for the Big-Means Clustering Algorithm
This study focuses on the optimization of the Big-means algorithm for clustering large-scale datasets, exploring three distinct parallelization...
-
Causal Transfer Evidential Clustering
Classical prototype-based clustering algorithms usually cannot achieve satisfactory results when the data is insufficient. Transfer learning can be...
-
A novel graph-theoretical clustering approach to find a reduced set with extreme solutions of Pareto optimal solutions for multi-objective optimization problems
Multi-objective optimization problems and their solution algorithms are of great importance as single-objective optimization problems are not usually...
-
A robust correlation coefficient for fermatean fuzzy sets based on spearman’s correlation measure with application to clustering and selection process
Fermatean fuzzy set (FFS) is an advance variant of fuzzy set applicable in curbing uncertainties and vagueness in complex decision making scenarios....
-
PTAS for Problems of Vector Choice and Clustering with Various Centers
AbstractWe consider two problems that are close in terms of formulation. The first one is that of clustering, i.e., partitioning the set of
... -
Sketch-based multiplicative updating algorithms for symmetric nonnegative tensor factorizations with applications to face image clustering
Nonnegative tensor factorizations (NTF) have applications in statistics, computer vision, exploratory multi-way data analysis, and blind source...
