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  1. 1
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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  2. 2
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  3. 3
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…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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  4. 4
    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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  5. 5
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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  6. 6
    Optimal finite- time prescribed performance of servo pneumatic positioning with PID control tuning using an evolutionary mating algorithm

    Optimal finite- time prescribed performance of servo pneumatic positioning with PID control tuning using an evolutionary mating algorithm by Addie Irawan, Hashim, M. H., Sulaiman, Mohd Iskandar Putra, Azahar

    Published 2023
    “…The design objective is to optimize the convergence rate and finite time of the prescribed performance function in error transformation in parallel with PID controller’s gains. …”
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  7. 7
    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…Modification and simplification using parallel processing are done for both methods to grossly search the optimal solution and to minimize the program running time, respectively. …”
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  8. 8
    Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions

    Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions by Hajighorbani, Shahrooz

    Published 2016
    “…In evaluation part, the DSMPP algorithm has been compared with two other methods.According to both simulation and experimental results, by implementing the DSMPP technique, the GMPP can be obtained faster. …”
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  9. 9
    A basic study on hybrid systems for small race car to improve dynamic performance using lap time simulation

    A basic study on hybrid systems for small race car to improve dynamic performance using lap time simulation by Kobayashi, Ikkei, Ogawa, Kazuki, Uchino, Daigo, Ikeda, Keigo, Kato, Taro, Endo, Ayato, Mohamad Heerwan, Peeie, Narita, Takayoshi, Kato, Hideaki

    “…The realization of the proposed hybrid system requires independent control algorithms for the two power systems, engine and electric motor, that take into consideration the state of the vehicle and the driver’s input; this system can be assumed to be a servo model system with multiple inputs and outputs and analyzed to obtain the optimal operation algorithm. …”
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  10. 10
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  11. 11
    An Improved Fuzzy Parallel Distributed –Like Controller for Multi-Input Multi-Output Twin Rotor System

    An Improved Fuzzy Parallel Distributed –Like Controller for Multi-Input Multi-Output Twin Rotor System by Mahmoud, Thair Sh.

    Published 2009
    “…The conclusion of this work is improving FLC response by using STFPDC and reducing the number of rules used to achieve this improvement by using ANFIS based on FSCM modeling. For future works, it is recommended to develop an optimization algorithm which achieves best selection for the range of influence which gives best response with less number of rules.…”
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  12. 12
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  13. 13
    Design of field programmable gate array-based proportional-integral-derivative fuzzy logic controller with tunable ganin

    Design of field programmable gate array-based proportional-integral-derivative fuzzy logic controller with tunable ganin by Obaid, Zeyad Assi

    Published 2010
    “…This block involves a tuning via scaling the universe of discourse and is able to accept optimal scaling gains. The particle swarm optimization method (PSO) is used to obtain the optimal values of these gains. …”
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  14. 14
    Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali

    Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali by Waleeda Swaidan, Ali

    Published 2015
    “…To establish a direct method, an efficient new algorithm is proposed to solve nonlinear optimal control problems with a finite time horizon under inequality constraints. …”
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  15. 15
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  16. 16
    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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  17. 17
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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  18. 18
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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  19. 19
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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  20. 20
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    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

    Published 2022
    “…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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