Search Results - (( java implementation search algorithm ) OR ( using clusters using algorithm ))
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1
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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2
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
3
Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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4
Songs Search Using Human Humming Voice
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Final Year Project -
5
Visualisation tool to study malaria transmission using network modelling
Published 2014“…In addition, the Hypertext Induced Topical Search (HITS) web search algorithm was adapted to implement a search engine, which uses the bipartite contact network as the input. …”
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Final Year Project Report / IMRAD -
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A review: accuracy optimization in clustering ensembles using genetic algorithms
Published 2011“…This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.…”
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7
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. …”
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Thesis -
8
An enhanced cluster head selection algorithm for routing in mobile AD-HOC network
Published 2017“…This thesis proposes a cluster based routing protocol, the Enhanced Cluster Routing Protocol (ECRP), which uses a modified cluster formation algorithm to build the cluster structure and select one of the nodes to be the cluster head. …”
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9
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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10
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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11
Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster
“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…Some clustering algorithms, especially those that are partitioned-based, clusters any data presented to them even if similar features do not present. …”
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13
Extensions to the K-AMH algorithm for numerical clustering
Published 2018“…It can also be used to cluster numerical values with minimum modification to the original algorithm. …”
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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. …”
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15
Clustering of rainfall data using k-means algorithm
Published 2019“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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Conference or Workshop Item -
16
Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz
Published 2010“…There are many techniques of clustering the image. The most widely used of clustering technique is Fuzzy C-Means algorithm (FCM). …”
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17
Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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Thesis -
18
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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19
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). …”
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20
Autonomous and deterministic supervised fuzzy clustering
Published 2010“…The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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