Search Results - (( development problem clustering algorithm ) OR ( java implication based algorithm ))
Search alternatives:
- development problem »
- implication based »
- java implication »
-
1
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
Get full text
Get full text
Thesis -
2
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…Thus in this study we intend to overcome these problems by determining a feature subset and the number of the cluster problems after developing an algorithm which simultaneously solved these issues. …”
Get full text
Get full text
Get full text
Thesis -
3
An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…However, existing density-based data stream clustering algorithms are not without problems. The first problem refers to the high computation time required for the clustering process. …”
Get full text
Get full text
Get full text
Thesis -
4
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…Throughout the years, considerable efforts made to tackle the clustering problem. Yet, because of the nature of the clustering problem, finding an efficient clustering optimization algorithm with reasonable performance is still an open challenge. …”
Get full text
Get full text
Thesis -
5
Image clustering comparison of two color segmentation techniques
Published 2010“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
6
Improved clustering using robust and classical principal component
Published 2017“…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
Get full text
Get full text
Thesis -
7
Data clustering using the bees algorithm
Published 2007“…K-means clustering involves search and optimization. The main problem with this clustering method is its tendency to converge to local optima. …”
Get full text
Get full text
Conference or Workshop Item -
8
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Clustering problem is discussed as a problem of non-smooth, non-convex optimization and a new method for solving this optimization problem is developed. …”
Get full text
Get full text
Thesis -
9
Cauchy Density-based Algorithm for VANETs Clustering in 3D Road Environments
Published 2022“…This paper tackles the problem of 3D VANETs using a centralized clustering model based on the developed Cauchy density model. …”
Get full text
Get full text
Article -
10
MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016“…Density-based method has emerged as a worthwhile class for clustering data streams. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
Get full text
Get full text
Article -
11
Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…According to the literature, crowding distance is one of the most efficient algorithms that was developed based on density measures to treat the problem of selection mechanism for archive updates. …”
Get full text
Get full text
Get full text
Article -
12
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
Get full text
Get full text
Thesis -
13
Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
14
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
Get full text
Get full text
Thesis -
15
Computational Discovery of Motifs Using Hierarchical Clustering Techniques
Published 2008“…A mismatch based hierarchical clustering algorithm is proposed in this paper, where three heuristic rules for classifying clusters and a post-processing for ranking and refining the clusters are employed in the algorithm. …”
Get full text
Get full text
Get full text
Proceeding -
16
Optimized clustering with modified K-means algorithm
Published 2021“…However, the choice of k is a prominent problem in the process of the k-means algorithm. In most cases, for clustering huge data, k is pre-determined by researchers and incorrectly chosen k, could end with wrong interpretation of clusters and increase computational cost. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
17
Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan
Published 2019“…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
Get full text
Get full text
Thesis -
18
Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…In general, the process of fake news detection was conducted in two different phases, the topic detection phase using a graph-based unsupervised clustering method based on HFPA and Markov Clustering Algorithm (MCL) called (HFPA-MCL) and the fake news detection phase using an unsupervised clustering method based on K-means algorithm. …”
Get full text
Get full text
Get full text
Thesis -
19
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…In this research, we applied SDAA to solve the constrained engineering problems and introduce an efficient data clustering algorithm which is hybrid of K-means and SDAA. …”
Get full text
Get full text
Get full text
Thesis -
20
Clustering High Dimensional Data Using Subspace And Projected Clustering Algorithms
Published 2010“…Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. …”
Get full text
Get full text
Get full text
Article