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  1. 1
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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  2. 2
    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization

    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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  3. 3
    Classification with degree of importance of attributes for stock market data mining

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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  4. 4
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Rahim At Samsuddin, H. A., Ab. Rahman, A. A. H., Andaljayalakshmi, G., Ahmad, R. B.

    Published 2008
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  5. 5
    Single and Multiple variables control using Tree Physiology Optimization

    Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

    Published 2017
    “…This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. …”
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  6. 6
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Hasliza, A. Rahim@Samsuddin, Ab Rahman, A. A H, Andaljayalakshmi, G., R. Badlishah, Ahmad, Wan Nur Suryani Firuz, Wan Ariffin

    Published 2009
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  7. 7
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Hasliza, A. Rahim@Samsuddin, Ab Al-Hadi, Ab Rahman, Andaljayalakshmi, G., R. Badlishah, Ahmad, Wan Nur Suryani Firuz, Wan Arrifin

    Published 2009
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  8. 8
    Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree

    Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree by Hasliza, A. Rahim@Samsuddin, Ab Al-Hadi, Ab Rahman, R. Badlishah, Ahmad, 'Aini Syuhada, Md Zain, M.I., Ahmad, Wan Nur Suryani Firuz, Wan Arrifin

    Published 2009
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  9. 9
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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  10. 10
    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system

    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

    Published 2021
    “…BST has been used to store the paths that Dijkstra algorithm initialled. …”
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  11. 11
    Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks

    Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Anwar, Farhat, Ahmed, Gharib Subhi Mahmoud

    Published 2015
    “…Thus this paper proposes a Differential Evolution based optimized mobile multicast routing algorithm for the shared tree architecture. …”
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  12. 12
    Decision tree-based approach for online management of PEM fuel cells for residential application

    Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

    Published 2004
    “…A database is extracted from a previously-performed Genetic Algorithm (GA)-based optimization has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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  13. 13
    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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  14. 14
    Amtree Protocol Enhancement by Multicast Tree Modification and Incorporation of Multiple Sources

    Amtree Protocol Enhancement by Multicast Tree Modification and Incorporation of Multiple Sources by Al‐Sharafi, Ali Mohammed Ali

    Published 2008
    “…By modifying the multicast tree, the number of nodes to be optimized was reduced. …”
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  15. 15
    Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm

    Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm by Sia, Florence Fui Sze, Rayner Alfred

    Published 2022
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  16. 16
    Decision tree-based approach for online management of pem fuel cells for residential application

    Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

    Published 2004
    “…A database was extracted from a previously�performed Genetic Algorithm (GA)-based optimization that has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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  17. 17
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  18. 18
    Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan

    Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan by Misnan, Azizi

    Published 1997
    “…A depth - first search algorithm is used to search for optimal chaining. Theorems on number of branches needed to be explored at each node of search tree are derived. …”
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  19. 19
    An optimized attack tree model for security test case planning and generation

    An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

    Published 2018
    “…By leveraging on the optimized attack tree algorithm used in this research work, the threat model produces efficient test plans from which adequate test cases are derived to ensure a secured web application is designed, implemented and deployed. …”
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  20. 20
    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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