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  1. 1
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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  2. 2
    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem

    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…A test suite of twelve optimization benchmark test functions and three global optimization problems (Team Formation Optimization - TFO, Low Autocorrelation Binary Sequence - LABS, and Modified Condition/Decision Coverage - MC/DC test case generation) were solved using the proposed algorithm. …”
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  3. 3
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Abd Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  4. 4
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  5. 5
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Ab. Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  6. 6
    Adaptive DNA computing algorithm by using PCR and restriction enzyme

    Adaptive DNA computing algorithm by using PCR and restriction enzyme by Watanabe, Shinpei, Tsuboi, Yusei, Ibrahim, Zuwairie, Yamamoto, Tsuneto, Ono, Osamu

    Published 2004
    “…In this paper, we introduce a new adaptive DNA coinpitting algorithm by using Poiymcruse Chain Rearlion (PCR). …”
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  7. 7
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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  8. 8
    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm

    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

    Published 2017
    “…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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  9. 9
    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Theoretical analysis block-based matching criteria are adapted to FUHS16, UHDS16 and UHDS8 algorithms, which are based on search points technique. …”
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  10. 10
    An adaptive opposition-based learning selection: The case for jaya algorithm

    An adaptive opposition-based learning selection: The case for jaya algorithm by Nasser, Abdullah B., Kamal Z., Zamli, Hujainah, Fadhl, Ghanem, Waheed Ali H. M., Saad, Abdul-Malik H. Y., Mohammed Alduais, Nayef Abdulwahab

    Published 2021
    “…In the last decade, many OBL techniques have been established in the literature including the Standard-OBL, General-OBL, Quasi Reflection-OBL, Centre-OBL and Optimal-OBL. Although proven useful, much existing adoption of OBL into meta-heuristic algorithms has been based on a single technique. …”
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  11. 11
    An Adaptive Immune Algorithm based Gravimetric Fluid Dispensing Machine

    An Adaptive Immune Algorithm based Gravimetric Fluid Dispensing Machine by Yap, David F. W.

    Published 2012
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  12. 12
    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm

    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

    Published 2019
    “…The reason is that the T-way sequence input interaction is NP-Hard problem. In this research, Fish Swarm algorithm is proposed to adapt with T-way sequence input interaction test strategy. …”
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  13. 13
    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems

    Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

    Published 2014
    “…The algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. …”
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  14. 14
    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network

    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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  15. 15
    Direct Adaptive Predictive Control For Wastewater Treatment Plant

    Direct Adaptive Predictive Control For Wastewater Treatment Plant by Shair, Ezreen Farina, Abu Bakar, Norazhar, Mohd Nor, Arfah Syahida, Mohd Azam, Sazuan Nazrah, Mohd Sobran, Nur Maisarah, Zainal Abidin, Amar Faiz

    Published 2012
    “…The adaptive control structure is based on the linear model of the process and combined with numerical algorithm for subspace state space system identification (N4SID). …”
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  16. 16
    Antenna arrays in multi-user detection of spread spectrum signals

    Antenna arrays in multi-user detection of spread spectrum signals by Karim, M.R., Wei, S.

    Published 2007
    “…A number of multi-user detection algorithms have been suggested by various authors. Optimal receivers based upon maximum likelihood sequence decoding are quite complex, their complexity increasing exponentially with the number of users in the system. …”
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  17. 17
    Computational methods for self-assembly of DNA nanostructures / Ong Hui San

    Computational methods for self-assembly of DNA nanostructures / Ong Hui San by Ong, Hui San

    Published 2016
    “…Several approaches have been adopted including development of an autonomous tool that incorporated evolutionary optimization algorithm in constructing these heterogeneous DNA shapes and the application of heuristic through undirected graph theory as an annotation schema to produce the connectivity maps. …”
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  18. 18
    Unequal error protection of H.264/AVC video transmitted over wireless network

    Unequal error protection of H.264/AVC video transmitted over wireless network by Rima, Boudjadja, Mohamed, Azni, Nadjib, Zennir M.

    Published 2015
    “…This work focus on the problem linked to the transmission of real time video over packet wireless network.Our objective is to define mechanism able to insuring a quality of video in spite to the problems of packet losses and transmission delays characterizing this type of network.The proposed mechanism is based Forward Error Correction (FEC) compatible with the H.264/AVC standard.This mechanism relies on a ratedistortion algorithm controlling the channel rates under a global rate constraint given by the network.This optimization takes into account the type of packet and his length; the tool of data portioning is used in our proposition.This mechanism leading to an unequal error protection of different units of coded sequence.A Reed-Solomon channel coding in application layer is adapted to unequal protected data.The experimentation results indicate the efficiency of our proposition compared to the equal error protection.…”
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  19. 19
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. …”
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  20. 20
    A systematic review of recurrent neural network adoption in missing data imputation

    A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

    Published 2025
    “…Performance metrics such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Area Under the Receiver Operating Characteristic Curve (AU-ROC), Mean Squared Error (MSE), and Mean Relative Error (MRE) are commonly used to evaluate these models. Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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