Search Results - (( java simulation optimization algorithm ) OR ( quality problem clustering algorithm ))

An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

“…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. …”
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Comparison of clustering algorithms on air quality substances in Peninsular Malaysia / Sitti Sufiah Atirah Rosly, Balkiah Moktar and Muhamad Hasbullah Mohd Razali by Rosly, Sitti Sufiah Atirah, Moktar, Balkiah, Mohd Razali, Muhamad Hasbullah

“…The output of K - means clustering algorithm shows that it can cluster the area into two clusters, namely as cluster 0 and cluster 1. …”
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MuDi-Stream: A multi density clustering algorithm for evolving data stream by Amini, A., Saboohi, H., Herawan, T., Teh, Y.W.

“…However, existing density-based data stream clustering algorithms are not without problem. There is a dramatic decrease in the quality of clustering when there is a range in density of data. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Meta-heuristic algorithm has been successfully implemented on data clustering problems seeking a near optimal solution in terms of quality of the resultant clusters. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Genetic algorithms are well known methods with high ability to resolve optimization problems including clustering. …”
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USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

“…It is one of problems in document clustering that decreases the cluster quality performance including f-measure, entropy and accuracy. …”
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Transitive fuzzy similarity multigraph-based model for alternative clustering in multi-criteria group decision making problems by Khameneh, Azadeh Zahedi, Kilicman, Adem, Md Ali, Fadzilah

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Discovering optimal clusters using firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…The simulation is implemented with iFogSim and java programming language. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…The swmcan-jg algorithm effectively tackles both noise and independence problems simultaneously.…”
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Nature inspired data mining algorithm for document clustering in information retrieval by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Various clustering techniques have been reported, but the effectiveness of most techniques relies on the initial value of k clusters.Such an approach may not be suitable as we may not have prior knowledge on the collection of documents.To date, there are various swarm based clustering techniques proposed to address such problem, including this paper that explores the adaptation of Firefly Algorithm (FA) in document clustering. …”
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A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

“…The experimental results revealed that the modified πRKM algorithm significantly affected the partitions quality of the cluster obtained. …”
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A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L.

“…Clustering evaluation techniques are important to check the clustering algorithm quality. …”

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…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. …”
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Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…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. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Methodology for modified whale optimization algorithm for solving appliances scheduling problem by Omar, Mohd Faizal, Mohd Bakeri, Noorhadila, Mohd Nawi, Mohd Nasrun, Hairani, Norfazlirda, Khalid, Khalizul

“…Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. …”
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Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

“…Falls are serious problem which lead to negative consequences on the quality of life especially for older people. …”
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Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.