Search Results - (( developing _ clustering algorithm ) OR ( java application during algorithm ))
Search alternatives:
- application during »
- java application »
- during algorithm »
-
1
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
Get full text
Get full text
Thesis -
2
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 -
3
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
Get full text
Get full text
Thesis -
4
A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
Published 2007“…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
Get full text
Get full text
Get full text
Book Section -
5
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 -
6
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 -
7
Development of an effective clustering algorithm for older fallers
Published 2022“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
Get full text
Get full text
Article -
8
Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
Get full text
Get full text
Conference or Workshop Item -
9
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 -
10
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 -
11
Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study
Published 2017“…These approaches of clustering algorithms whether Distributed, Centralized, or Hybrid are reviewed very well, since the most of clustering algorithms have been developed by many researches based on these approaches. …”
Get full text
Get full text
Get full text
Article -
12
The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
Get full text
Get full text
Thesis -
13
Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Therefore, Genetic Algorithm-Cuckoo Search (GACS) is proposed and developed based on the multi-hop clustering model in this paper. …”
Get full text
Get full text
Article -
14
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
15
Optimizing wireless sensor networks: A survey of clustering strategies and algorithms
Published 2024“…This study serves as a helpful source of knowledge that can encourage the further development of the enhancement of clustering algorithms for WSNs in response to modern technology needs.…”
Get full text
Get full text
Get full text
Article -
16
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 -
17
-
18
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 -
19
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2009“…In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less subclass number, stability and bounded time of classi¯cation with respect to the variable data size. …”
Get full text
Get full text
Citation Index Journal -
20
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2008“…In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less subclass number, stability and bounded time of classi¯cation with respect to the variable data size. …”
Get full text
Get full text
Citation Index Journal