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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
    Study Of EMG Feature Selection For Hand Motions Classification

    Study Of EMG Feature Selection For Hand Motions Classification by Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Too, Jing Wei

    Published 2019
    “…Thus, this paper employs two recent feature selection methods namely competitive binary gray wolf optimizer (CBGWO) and modified binary tree growth algorithm (MBTGA) to evaluate the most informative EMG feature subset for efficient classification. …”
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  4. 4
    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang

    Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

    Published 2013
    “…Discrete Tchebichef moments are selected as the implementation platform of the proposed algorithms.To evaluate the performance of invariant algorithms, empirical studies have been carried out on large set of binary images which consist of numbers, English letters, symbols, Chinese characters and objects like animals, trees and company logos under noiseless and noisy conditions. …”
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  5. 5
    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA

    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

    Published 2025
    “…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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  6. 6
    A-star (A*) algorithm implementation for robotics path planning navigation

    A-star (A*) algorithm implementation for robotics path planning navigation by Emirul Ridzwan, Nor Azmi

    Published 2018
    “…This thesis is about the implementation of Astar (A*) algorithm as path planning algorithm used in robotics navigation. …”
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  7. 7
    Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah

    Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah by Hanafiah, Sukri

    Published 1997
    “…The euler's path it using pseudo input and Heuristic algorithm to find the minimum interlace. …”
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  8. 8
    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm

    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm by Krishnan P.S., Paw J.K.S., Kiong T.S.

    Published 2023
    Conference Paper
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  9. 9
    Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection

    Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

    Published 2024
    “…Therefore, this binary tree cannot analyse complex features of mixed attributes and restricts the CART tree's deep-level feature recognition ability. …”
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  10. 10
    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group

    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group by Azali Saudi, Jumat Sulaiman

    Published 2014
    “…Consequently, the gradient of the potential functions would be used by the searching algorithm to generate path from starting to goal location. …”
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  11. 11
    False path identification algorithm framework for nonseparable controller-data path circuits

    False path identification algorithm framework for nonseparable controller-data path circuits by Shaheen, Ateeq U. R., Hussin, Fawnizu Azmadi, Hamid, Nor Hisham

    Published 2016
    “…This paper proposes an algorithm frame-work to deal with these false paths through identification for DFT test. …”
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  12. 12
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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  13. 13
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…These problems were extensively studied within the scope of classification (binary and multi-class) and regression (linear and survival). …”
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  14. 14
    False path identification algorithm framework for nonseparable controller-data path circuits

    False path identification algorithm framework for nonseparable controller-data path circuits by Shaheen, A.-U.-R., Hussin, F.A., Hamid, N.H.

    Published 2017
    “…This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. …”
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  15. 15
    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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  16. 16
    A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers

    A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers by Ahmed I.T., Hammad B.T., Jamil N.

    Published 2025
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  17. 17
    Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries

    Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries by Fadzli, S.A., Abdulkadir, S.I., Makhtar, M., Jamal, A.A.

    Published 2016
    “…The path computed using the classic Dijkstra's algorithm is the shortest; however, it may not be the most feasible. …”
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  18. 18
    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA

    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Hui, Bian, Chiew, Kang Leng

    Published 2025
    “…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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  19. 19
    Indoor path planning using harmonic functions via half-sweep arithmetic mean method

    Indoor path planning using harmonic functions via half-sweep arithmetic mean method by Azali Saudi, Jumat Sulaiman

    Published 2019
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  20. 20
    Pixel-based feature for android malware family classification using machine learning algorithms

    Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

    Published 2021
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