Search Results - (( data integration clustering algorithm ) OR ( java application optimization algorithm ))

Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

“…This paper proposes a clustering method that integrates the simplicity of the k-means algorithm with the capability of the Bees Algorithm to avoid local optima. …”
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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

“…The first modification is the integration of BH algorithm and levy flight, which result in data clustering method, namely “Levy Flight Black Hole (LBH)”. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

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Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

“…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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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Automatic clustering of gene ontology by genetic algorithm by Othman, Razib M., Deris, Safaai, Zakaria, Zalmiyah, Illias, Rosli M., Mohamad, Saberi M.

“…Abstract—Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

“…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

The performance of k-means clustering method based on robust principal components by Kadom, Ahmed, Midi, Habshah, Rana, Sohel

“…It is now evident that clustering results can be improved by applying classical principal component analysis (PCA) with the k-means clustering algorithm. …”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

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A hybrid of fuzzy c-means clustering and Latent Dirichlet Allocation for analysing philanthropic corporate social responsibility activities / Nik Siti Madihah Nik Mangsor by Nik Mangsor, Nik Siti Madihah

“…This study has extended document clustering technique by integrating the traditional document clustering application with topic modeling approach. …”
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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

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks by Alhalabi, Huda A. H.

“…A Multi-Hop Selective Constructive Interference Flooding (MSCIF) protocol is proposed to address the problem of low connectivity in WSNs with a sparse distribution and improve the network’s lifetime. MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. …”
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Data dissemination in VANETs using clustering and probabilistic forwarding based on adaptive jumping multi-objective firefly optimization by Hamdi, Mustafa Maad, Audah, Lukman, Rashid, Sami Abduljabbar

“…This developed multi-objective optimization was designated as adaptive jumping multi-objective firefly algorithm (AJ-MOFA). Afterwards, AJ-MOFA was integrated with a clustering and forwarding mechanism (CFM). …”
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