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  1. 1

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  2. 2

    Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

    Published 2018
    “…The pattern search is an optimization algorithm that further optimizes the values obtained in the maximum iterations of standard FA. …”
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    Article
  3. 3

    Optimal point-to-point trajectory tracking of redundant manipulators using generalized pattern search by Ata, Atef A, Myo, ThiRein

    Published 2005
    “…The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. …”
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  4. 4

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Search pattern, search strategy and initial center are the main factors that contribute to the performance in the searching process. …”
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  5. 5

    Application of pattern search method to economic load dispatch with valve point loading / Siti Aisah Md. Sari by Md. Sari, Siti Aisah

    Published 2010
    “…This study presents the application of Pattern Search (PS) method in Economic Dispatch (ED) problem; ED is used to optimize the fuel cost of electric energy while at the same time allocate the demand between available generation unit. …”
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  6. 6

    Interference reduction by null-forming optimization based MVDR technique using gravitational search algorithm by Shahab, Suhail Najm, Ayib Rosdi, Zainun, Alabdraba, Waleed M. Sh., Nurul Hazlina, Noordin

    Published 2017
    “…In the present work, Gravitational Search Algorithm (GSA) is a new modern metaheuristic optimization technique used for optimizing the MVDR null-forming level by controlling the excitation weight coefficients in a linear antenna array radiation pattern synthesis. …”
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  7. 7
  8. 8

    Performance optimization on axial-flux permanent magnet coreless generator using novel hybrid computational method based on genetic algorithm and pattern search / Lok Choon Long by Lok , Choon Long

    Published 2016
    “…Complex real-world problems can be solved by heuristic optimization efficiently. Improved hybrid optimization method using Pattern Search (PS) and Genetic Algorithm (GA) onto Axial-Flux Permanent Magnet (AFPM) Coreless generator is presented in this thesis, and the optimization is based on the popular multi-objective sizing equation. …”
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    Thesis
  9. 9

    Using Pattern Search Methods for Minimizing Clustering Problems by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June, Mohagheghtabar, Maryam

    Published 2010
    “…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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    Article
  10. 10
  11. 11

    Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

    Published 2023
    “…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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  12. 12

    Nature-Inspired Heuristic Frameworks Trends in Solving Multi-objective Engineering Optimization Problems by Chang C.C.W., Ding T.J., Ee C.C.W., Han W., Paw J.K.S., Salam I., Bhuiyan M.A.S., Kuan G.S.

    Published 2025
    “…These algorithms are inspired and modelled based on the searching behaviour of animals in real life. …”
    Review
  13. 13

    The effect of job satisfaction on the relationship between organizational culture and organizational performance by Imran, Muhammad

    Published 2023
    “…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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  14. 14

    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
    Review
  15. 15

    Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

    Published 2017
    “…The more number of marbles, the higher the search accuracy. In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
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  16. 16

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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    Article
  17. 17

    An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

    Published 2019
    “…To improve exploration performance of the individual agent, a turning angle limit and boundary reflection is introduced in DLF. In order to optimize search space exploration and to maintain inter-robot communication connectivity at swarm level, a dispersion algorithm based on attraction and repulsion force is proposed. …”
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  18. 18

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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  19. 19

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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  20. 20

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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    Conference or Workshop Item