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  1. 1
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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  2. 2
    Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

    Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints by Abdullah, M.N., Bakar, Ab Halim Abu, Rahim, N.A., Mokhlis, Hazlie, Illias, Hazlee Azil, Jamian, J.J.

    Published 2014
    “…Simulation results found that the proposed MPSO-TVAC algorithm has good solution quality and more robust than other methods reported in previous work.…”
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  3. 3
    Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization

    Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
    “…Artificial immune system (AIS) is one of the nature-inspired algorithm for solving optimization problems. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability compare to other meta-heuristic methods. …”
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  4. 4
    Artificial immune system based remainder method for multimodal mathematical function optimization

    Artificial immune system based remainder method for multimodal mathematical function optimization by Yap D.F.W., Koh S.P., Tiong S.K.

    Published 2023
    “…Artificial immune system (AIS) is one of the nature-inspired algorithm for solving optimization problems. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability compare to other meta-heuristic methods. …”
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  5. 5
    Application of Evolutionary Algorithm for Assisted History Matching

    Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

    Published 2014
    “…While the automatic method focus on optimization which is normally computer based. …”
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  6. 6
    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM

    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM by HO JOON , HENG

    Published 2012
    “…So, this paper will introduce Bacterial Foraging Optimization Algorithm (BFOA) in optimizing the parameters for PI control. …”
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  7. 7
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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  8. 8
    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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  9. 9
    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…An improved method that is based of the combination of Gardner transformation, optimal compensation deconvolution, and signal modelling techniques is suggested in this paper. …”
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  10. 10
    Block based low complexity iterative QR precoder structure for Massive MIMO

    Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

    Published 2021
    “…For the system sum rate, the results of the increase in the number of users with a fixed number of 128 and 512 BS antennas show that the proposed method achieved up to 24% and 35% respectively compared to the regular BD algorithm. …”
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  11. 11
    Modification to queueing system M/M/1 with Blum-Blum-Shub generator

    Modification to queueing system M/M/1 with Blum-Blum-Shub generator by Jaffara, M. Z. A. M., Joey, L. F. L.

    Published 2022
    “…In this paper, the researchers modified a type of queueing model simulation which is called ‘M/M/1’ by using a part of Blum-Blum-Shub algorithm. …”
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  12. 12
    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution

    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution by Lau, Kia Li

    Published 2019
    “…Meanwhile, the Artificial Neural Network (ANN) was simulated from experimental data and applied to optimize, develop and create prediction models for boron adsorption by AO-modified poly(AN-co-AA). …”
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  13. 13
    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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  14. 14
    A novel islanding detection technique using modified Slantlet transform in multi-distributed generation

    A novel islanding detection technique using modified Slantlet transform in multi-distributed generation by Hizam, Hashim, Ahmadipour, Masoud, Mohd Radzi, Mohd Amran, Othman, Mohammad Lutfi, Chireh, Nikta

    Published 2019
    “…A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. …”
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  15. 15
    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi

    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi by Seyed Hossein, Mahdavi

    Published 2016
    “…Accordingly, in the second part of this research, the procedure of structural identification and damage detection has been developed by employing the wavelet-based method through the modified genetic algorithms (GAs) to optimally solve inverse problems. …”
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  16. 16
    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator

    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2021
    “…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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  17. 17
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Testing on real data sets showed consistency results as the simulated ones. Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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  18. 18
    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator

    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2021
    “…The modified algorithm is called Discrete Simulated Kalman Filter Optimizer (DSKFO). …”
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  19. 19
    A Modified Gravitational Search Algorithm for Discrete Optimization Problem

    A Modified Gravitational Search Algorithm for Discrete Optimization Problem by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Shahdan, Sudin, Sophan Wahyudi, Nawawi, Amar Faiz, Zainal Abidin, Muhammad Arif, Abdul Rahim, Kamal, Khalil

    Published 2014
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  20. 20
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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