Search Results - (( strategy implementation clustering algorithm ) OR ( java application optimized algorithm ))

An Effective Power Dispatch Strategy for Clustered Microgrids While Implementing Optimal Energy Management and Power Sharing Control Using Power Line Communication by Ahmed Mohamed, Ahmed Haidar, Adila, Fakhar, Kashem M., Muttaqi

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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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An Effective Power Dispatch Strategy for Clustered Micro-grids while Implementing Optimal Energy Management and Power Sharing Control using Power Line Communication by Ahmed Mohamed, Ahmed Haidar, Adila, Fakhar, Muttaqi, Kashem M

“…This paper proposes an effective power dispatch strategy for clustered micro-grids. The developed hybrid algorithm implements optimal energy management and power sharing control using binary data. …”
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Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm by Nor, N.H.M., Daud, H., Ullah, S.

“…Parametric assumptions commonly implemented in most of algorithm in cluster detections. …”
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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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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…For floor localisation, the strategy is based on developing the algorithm to determine the floor by utilising fingerprint clustering technique. …”
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Application model of k-means clustering: Insights into promotion strategy of vocational high school by Abadi S., Mat The K.S., Nasir B.M., Huda M., Ivanova N.L., Sari T.I., Maseleno A., Satria F., Muslihudin M.

“…Data mining techniques in this initiative were applied to achieve in determining the promotional strategy. Using Clustering K-Means algorithm, it is one method of non-hierarchical clustering data in classifying student data into multiple clusters based on similarity of the data, so that student data that have the same characteristics are grouped in one cluster and that have different characteristics grouped in another cluster. …”

Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

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Enhancing Performance of Batik SMEs through Cleaner Production Adoption: Insights from Clustering Algorithm Analysis by Achmad, Fandi, Zulkarnain, Ibnu, Rumanti, Augustina Asih, Wiratmadja, Iwan Inrawan, Shuhidan, Shuhaida Mohamed

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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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Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach by Ullah, S., Daud, H., Dass, S.C., Khan, H.N., Khalil, A.

“…To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

“…Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

“…Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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Benchmarking Framework for Performance in Load Balancing Single System Image by S. Ahmed, Bestoun

“…There is an essential need for a benchmark framework for the Single System Image clusters due to the wide range of implementation and the need for identifying the performance and behaviour of the system. …”
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Stock prediction by applying hybrid Clustering-GWO-NARX neural network technique by Das, Debashish, Sadiq, Ali Safa, Mirjalili, Seyedali

“…It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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Hybrid clustering-GWO-NARX neural network technique in predicting stock price by Das, Debashish, Sadiq, Ali Safa, Mirjalili, Seyedali, Noraziah, Ahmad

“…It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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