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  1. 1
    A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network

    A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Roslina, Abd Hamid

    Published 2015
    “…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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  2. 2
    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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  3. 3
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  4. 4
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  5. 5
    Reactive memory model for ant colony optimization and its application to TSP

    Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2014
    “…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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  6. 6
    Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods

    Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods by Najihah, Mohamed, Ahmad Lutfi, Amri Ramli, Ahmad, Abd Majid, Abd Rahni, Mt Piah

    Published 2019
    “…Rational cubic Bézier curves are used to approximate the data sets while minimizing the least-squares error function using different metaheuristics algorithms. Those metaheuristics algorithms are Harmony Search, Genetic Algorithm, Particle Swarm Optimization and Modified Harmony Search. …”
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  7. 7
    Route optimization security in mobile IPv6 wireless networks: a test-bed experience

    Route optimization security in mobile IPv6 wireless networks: a test-bed experience by Mehdizadeh, Abbas, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir, Kurup, Gopakumar

    Published 2008
    “…This algorithm is able to detect and prevent the attacker from modifying the data with using an encryption algorithm by cost of little bit increase but tolerable delay. …”
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  8. 8
    Security enhancement of route optimization in mobile IPv6 networks

    Security enhancement of route optimization in mobile IPv6 networks by Mehdizadeh, Abbas, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir, Kurup, Gopakumar

    Published 2008
    “…This algorithm is able to detect and prevent the attacker from modifying the data with using an encryption algorithm by cost of little bit increase but tolerable delay. …”
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  9. 9
    A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm

    A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm by Yasin, Azman, M. Zeki, Akram, Mohammed, Ghassan N.

    Published 2013
    “…The quality of the watermarked images is considered as one of the most important requirements of any watermarking system.In most applications, the watermarking algorithm embeds the watermark without affecting the quality of the host media.In this study, a comparison of watermarking image quality was performed between two existing methods: Dual Intermediate Significant Bit (DISB) an d Genetic Algorithm (GA).The first method focuses on the high quality of the watermarked image based on DISB model and this method requires embedding two bits into every pixel of the original image, while the other six bits are modified so as to immediately assimilate the original pixel. …”
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  10. 10
    Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO

    Enhancement and assessment of WKS variance parameter for intelligent 3D shape recognition and matching based on MPSO by Naffouti, S.E., Aouissaoui, I., Fougerolle, Y., Sakly, A., Meriaudeau, F.

    Published 2017
    “…This paper presents an improved wave kernel signature (WKS) using the modified particle swarm optimization (MPSO)-based intelligent recognition and matching on 3D shapes. …”
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  11. 11
    Modeling the powder compaction process using the finite element method and inverse optimization

    Modeling the powder compaction process using the finite element method and inverse optimization by Hrairi, Meftah, Chtourou, Hedi, Gakwaya, Augustin, Guillot, Michel

    Published 2011
    “…Minimization of the objective function with respect to the material parameters was performed using an in-house optimization software shell built on a modified Levenberg–Marquardt method. …”
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  12. 12
    Use of AR Block Processing for Estimating the State Variables of Power System

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
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  13. 13
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…In addition, two novel Jaya-based methods namely, the modified Jaya (MJaya) algorithm and quasi-oppositional modified Jaya (QOMJaya) algorithm are proposed to solve different MOOPF problems. …”
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  14. 14
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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  15. 15
    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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  16. 16
    Optimized clustering with modified K-means algorithm

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

    Published 2021
    “…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  17. 17
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  18. 18
    Wind farm layout design using modified particle swarm optimization algorithm

    Wind farm layout design using modified particle swarm optimization algorithm by Rehman, S., Ali, S.S.A.

    Published 2015
    “…This paper proposes yet another optimization algorithm which is based on the particle swarm optimization (PSO) algorithm, which is a popular optimization algorithm. …”
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  19. 19
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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  20. 20
    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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