Search Results - parallel implementation ((using algorithm) OR (((means algorithm) OR (learning algorithm))))*

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN. …”
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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Parallel backpropagation neural network training for face recognition by Omarov B., Suliman A., Tsoy A.

“…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”

A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

“…Accordingly, this paper proposes a new parallel ensemble model comprising hybrid machine and deep learning for undertaking FDD tasks. …”
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Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

“…For commercial CFD packages, in many cases the solution algorithms are black boxes, even though parallel computing helps in many cases to overcome the limitations, as shown here. …”
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One-dimensional finite element discretization of crack propagation through parallel computation by Islam, Md. Rajibul, Alias, Norma

“…The parallel algorithm with parallel computer system has been used in order to perform the computational analysis of finite element for this study. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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New CFAR algorithm and circuit development for radar receiver by Kamal, Mustafa Subhi

“…Therefore, the MSS-CA-CFAR is chosen to implement by practical digital circuit and there is another important feature in the MSS-CFAR algorithm that is parallel processing since the spike selection process is done at the same time with summing of samples process that makes this algorithm much less in processing time from any other algorithm using the same environment. …”
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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

“…Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. …”
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A genetic-based HAC technique for parallel clustering of bilingual Malay-English corpora by Ng Zhen Wei, Chan Chen Jie, Rayner Alfred, Joe Henry Obit

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An Efficient Parallel Quarter-sweep Point Iterative Algorithm for Solving Poisson Equation on SMP Parallel Computer by M., Othman, A. R., Abdullah

“…However, the last two algorithms were found to be suitable for parallel implementation (Evans 1984) and Ali el at. (1997». …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

“…The parallel algorithm was developed using C language with the utilization of the Message Passing Interface (MPI) library. …”
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Implementation of a parallel XTS encryption mode of operation by Alomari, Mohammad Ahmed, Samsudin, Khairulmizam, Ramli, Abdul Rahman

“…In this paper, the IEEE XTS encryption mode of operation for storage encryption (P1619 standard) has been implemented using parallel design. A performance comparison between the sequential and parallel algorithms of XTS mode is presented here. …”
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Mitigation of atmospheric turbulences using mode division multiplexing based on decision feedback equalizer for free space optics by Almogahed, Abdullah, Amphawan, Angela, Fazea, Yousef

“…The implementation of the MMSE algorithm is used to optimize both the feedforward and the feedback filter coefficients of DFE. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Parallel implementation on improved error signal of backpropagation algorithm by Mohd Aris, Teh Noranis

“…The experiments are implemented using the Sequent Symmetry SE30 parallel machine. …”
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Parallel implementation on improved error signal of backpropagation algorithm by Mohd Aris, Teh Noranis, Sulaiman, Md. Nasir, Mohd Saman, Md. Yazid, Othman, Mohamed

“…Further study on the improved BP algorithm is carried out on many processors, which is implemented using the Sequent Symmetry SE30 machine. …”
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