Search Results - parallel selection ((bees algorithm) OR (modified algorithm))*

Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). …”
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Parallel computation of maass cusp forms using mathematica by Chan, Kar Tim

“…Our parallel programme comprises of two important parts namely the pullback algorithm and also the Maass cusp form algorithm. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

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A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm by Azmin, Farah Ayuni

“…This research proposed a modified regular shape which is based on the best selected regular shape, modified using genetic algorithm on the central processing unit (CPU). …”
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Diverse cell interaction in dynamic cell sizing and VC-PGA cell priority selection method by Amphawan, Angela, G, Ezra Moris Abraham

“…In this paper, the diverse interaction among cells is discussed.The preliminary description of forward link capacity gain on a single cell serves as groundwork for discussions on bi-directional impact of cell-pairs and the multifarious interactions of cells in a CDMA network.The diverse interaction of cells is then made analogous to that of community members in a virtual community in a genetic algorithm.The cell to be given highest priority cell over shrinking in the virtual community is selected by the virtual community parallel genetic algorithm (VC-PGA).By this method, the number of cell attenuations may be controlled, the emergence of coverage holes reduced and thus, the quality of service increased.…”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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Exploring the High Performance Computing-Enablement of a Suite of Gene-Knockout Based Genetic Engineering Applications by Li, Zhenya, Sinnott, Richard O., Choon, Yee Wen, Sjaugi, Muhammad Farhan, Mohd Saberi, Mohamad, Safaai, Deris, Suhaimi, Napis, Omatu, Sigeru, Corchado, Juan Manuel, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…Genetic engineering provides methods to modify the genes of microorganisms to achieve desired effects. …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

“…As a result of this mapping study, five major hybridization strategies were identified in which two-third of solutions have been based on modifying algorithm operators or integration with another metaheuristic. …”
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New methods of partial transmit sequence for reducing the high peak-to-average-power ratio with low complexity in the ofdm and f-ofdm systems by Abduljabbar, Yasir Amer

“…Third, a new hybrid method that combines the Selective mapping and Cyclically Shifts Sequences (SLM-CSS-PTS) techniques in parallel has been proposed for improving the PAPR reduction performance and the computational complexity level. …”
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An integrated priority-based cell attenuation model for dynamic cell sizing by Amphawan, Angela, Omar, Mohd Nizam, Din, Roshidi

“…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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