Search Results - (( data distributions clustering algorithm ) OR ( _ evaluation based algorithm ))

An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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A cluster-based hybrid replica control protocol for high availability in data grid by Mabni, Zulaile

“…This research has contributed a dynamic cluster-based hybrid replica control protocol which proposed a clustering algorithm to determine the number of clusters, a mechanism for dynamic participation of nodes in the network, and a replica placement algorithm that produces low communication cost and high data availability as compared to DH and DDG protocols. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems by Haneen, Abd Wahab, Noraziah, Ahmad, Alsewari, Abdulrahman A., Sinan, Q. Salih

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.] by Mohamed Noor, Noorhayati, Md Din, Norashidah, Kasiran, Zolidah, Khalid, Nor Azimah, Abdullah, Shapina

“…To evaluate the proposed clustering algorithm, the performance of sensor networks is compared with CogLEACH, LEACH and CHEF routing protocols. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs by Talib, Mohammed Saad, Abdullah, Nihad Ibrahim, Hassan, Aslinda, Abal Abas, Zuraida, Mohammed Al-Khazraji, Ali Abdul-Jabbar, Alamery, Thamer, Ibrahim, Ali Jalil

“…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…The methods are Byte Frequency Distribution, Entropy, and Rate of Change. Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study by Lai, Daphne Teck Ching, Owais A. Malik

“…Gower distance was used for measuring similarity for mixed data types. To evaluate the clusters found; cluster distribution and Silhouette index were used for cluster quality, Cohen's Kappa Index for cluster stability and Cramer's V Coefficient for clinical relevance of clusters. …”
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Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. …”
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ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

“…The proposed multi-trust approach is used to analyze the credibility of sensitive monitored data. A novel and efficient cluster head selection algorithm (ECHSA) is employed to improve the performance of the cluster head (CH) selection process in clustered WSN. …”
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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications by Chuan, Zun Liang, Tan, Lit Ken, Wee, Angel Chi Chyin, Yim Hin, Tham, Shao, Jie Ong, Jia, Yi Low, Chong, Yeh Sai

“…The proposed AI-based predictive algorithm aimed to provide predictive insights and interpret the impact of significant economic, environmental, and social clustered determinants on electricity consumption in Malaysia. …”
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An enhancement of path selection to cluster head based on multi-hop routing in two-tier wireless sensor network by Wan Isni Sofiah, Wan Din, Asyran Zarizi, Abdullah, Razulaimi, Razali, Ahmad Firdaus, Zainal Abidin, Salwana, Mohamad, Eh Phon, Danakorn Nincarean, Cik Feresa, Mohd Foozy

“…Currently, the data transmission from sensor nodes to the cluster head uses a single hop which consumes more energy; thus, in this paper the enhancement of previous algorithm, which is MAP, the data transmission will use several paths to reach the cluster head. …”
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Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

“…In multi hop communication, the Cluster Head (CH) has to send the aggregated data to one hop away neighbor cluster head either it is far away or near to the sink, while in a single hop it makes a difference. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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Evaluation of Clustering and Multi-hop Routing Protocols in Mobile Ad-hoc Sensor Networks by Jambli, M.N., Hendrick, A., Julaihi, A.A., Abdullah, J., Suhaili, S.M.

“…A HEED (Hybrid, Energy-Efficient, Distributed) is one of the clustering algorithm for sensor networks. In HEED, a node is elected to become a cluster head based on its residual energy and its communication cost in its neighbourhood. …”
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution by Nokhanji, Nooshin

“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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