Search Results - (( develop computing clustering algorithm ) OR ( java simulation optimization algorithm ))
Search alternatives:
- computing clustering »
- develop computing »
- java simulation »
-
1
MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016Get full text
Get full text
Article -
2
Computational Discovery of Motifs Using Hierarchical Clustering Techniques
Published 2008Get full text
Get full text
Get full text
Proceeding -
3
Data clustering using the bees algorithm
Published 2007“…One of the most popular clustering methods is k-means clustering because of its simplicity and computational efficiency. …”
Get full text
Get full text
Conference or Workshop Item -
4
-
5
Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
Article -
6
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
Get full text
Get full text
Thesis -
7
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
Get full text
Get full text
Article -
8
-
9
Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
10
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2009Get full text
Get full text
Citation Index Journal -
11
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2008Get full text
Get full text
Citation Index Journal -
12
An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
Get full text
Get full text
Get full text
Thesis -
13
-
14
-
15
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009Get full text
Get full text
Article -
16
Optimized clustering with modified K-means algorithm
Published 2021“…The proposed algorithm utilised a distance measure to compute the between groups’ separation to accelerate the process of identifying an optimal number of clusters using k-means. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
17
The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
Get full text
Get full text
Get full text
Get full text
Article -
18
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
Get full text
Get full text
Get full text
Thesis -
19
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
Get full text
Get full text
Get full text
Monograph -
20
Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
Get full text
Get full text
Article
