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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    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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  2. 2
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  3. 3
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  4. 4
    Optimization of multi-holes drilling path using particle swarm optimization

    Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

    Published 2022
    “…One way to improve the multi-hole drilling is by optimising the tool path in the process. This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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  5. 5
    Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization

    Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Yaseen, Zeher M.

    Published 2019
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  6. 6
    An improved gbln-pso algorithm for indoor localization problem in wireless sensor network

    An improved gbln-pso algorithm for indoor localization problem in wireless sensor network by Muhammad Shahkhir, Mozamir

    Published 2022
    “…This study aims to increase the accuracy of node estimation and to minimize time taken for the node localization process. To achieve the stated aims, we implemented an Improved Global best Local Neigborhood Particle Swarm Optimization (IGbLN-PSO) algorithm. …”
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  7. 7
    Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application

    Hardware Software Partitioning Using Particle Swarm Optimization (PSO) In Image Processing Application by Tan, Jia Zheng

    Published 2018
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  8. 8
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

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

    Published 2019
    “…Zero Motion Prejudgment is implemented as an additional approach to speed up the searching process hence could reduce computation performance. …”
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  9. 9
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  10. 10
    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

    Published 2017
    “…Agents interact among them to modify and enhance the solution throughout the search process. Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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  11. 11
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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  12. 12
    A swarm intelligent approach for multi-objective optimization of compact heat exchangers

    A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

    Published 2023
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  13. 13
    Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing

    Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing by S. Ahmed, Bestoun

    Published 2011
    “…Unlike other existing AI-based strategies, the lightweight computation of the particle swarm search process enables PSTG to support high interaction strengths of up to t=6. …”
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  14. 14
    Real-time system for facial emotion detection using GPSO algorithm

    Real-time system for facial emotion detection using GPSO algorithm by Bashir, Mohammed Ghandi, R., Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  15. 15
    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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  16. 16
    Chaotic ant swarm optimization for economic dispatch considering transmission losses / Amelia Abd Razak

    Chaotic ant swarm optimization for economic dispatch considering transmission losses / Amelia Abd Razak by Abd Razak, Amelia

    Published 2012
    “…This algorithm combines with the chaotic and selforganization behaviour ants in the foraging process. …”
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  17. 17
    A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm

    A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm by Ahmed Ali Mohammed, Al-saffar

    Published 2024
    “…The built DCCRNN is based on the Salp Swarm optimization Algorithm (SSA), a processor that given a particular dataset will find the best CRNN’s structure and hyperparameters. …”
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  18. 18
    Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment

    Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment by Gabi, Danlami, Ismail, Abdul Samad, Zainal, Anazida, Zakaria, Zalmiyah, Al-Khasawneh, Ahmad

    Published 2018
    “…In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. …”
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  19. 19
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  20. 20
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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