Search Results - (( java implementation modified algorithm ) OR ( using random clustering algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…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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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

“…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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Document clustering for knowledge discovery using nature-inspired algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

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Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

“…The performance of the proposed algorithm is compared with that of several common clustering algorithms using real-world datasets. …”
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Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows by Afzal, Asif, Aabid, Abdul, Khan, Ambareen, Khan, Sher Afghan, Rajak, Upendra, Verma, Tikendra Nath, Kumar, Rahul

“…Regression of both the pressures using a random forest classification algorithm is carried out. …”
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An Improved LEACH Algorithm Based On Fuzzy C-Means Algorithm And Distributed Cluster Head Selection Mechanism. by Hassan, Ali Abdul Hussian, Othman, Mohd Fairuz Iskandar, Md Shah, Wahidah, Husien, Ali Mohamed, Hassan, Hayder Abdul Hussien

“…In LEACH algorithm, the random manner is used to select specific nodes as a cluster heads. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Identifying clusters structure of rare events using random forest clustering by Zaturrawiah A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, Norhafiza Hamzah

“…To identify the intrinsic structures in the minority class (the stroke group), Random Forest Clustering was used to produce the proximity matrix and fed to Partition around Medoid (PAM) clustering method to identify the optimal number of clusters. …”
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Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification by Juma, Sundus, Muda, Zaiton, Yassin, Warusia

“…X-Means clustering is utilized to gather whole data into congruent cluster based on their behaviour whereas Random Forest classifier is utilized to rearrange the misclassified clustered data to apropos group. …”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

“…In this thesis, the accuracy of the proposed algorithm was evaluated using two standard online benchmarking database systems. …”
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A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering by Prasetyadi, Abdurrakhman, Nugroho, Budi, Tohari, Adrin

“…Nevertheless, it is difficult to obtain a homogeneous clustering result of the k-means method because this method is sensitive to a random selection of the centers of the cluster. …”
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An energy based cluster head selection unequal clustering algorithm with dual sink (ECH-DUAL) for continuous monitoring applications in wireless sensor networks by Alagirisamy, Mukil, Chow, Chee Onn

“…In this work, an energy based cluster head selection unequal clustering algorithm (ECH-DUAL) using dual (static and mobile) sink is proposed. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Exploring clusters of rare events using unsupervised random forests by Z A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, N Hamzah

“…To identify the intrinsic structures in the minority class (the stroke group), Random Forest Clustering was used to produce the proximity matrix and fed to Partition around Medoid (PAM) clustering method to identify the optimal number of clusters. …”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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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

“…Furthermore, the results revealed a high convergence rate, upon which the algorithm’s performance was subjected to data clustering problems and investigated using six real datasets. …”
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