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  1. 1
    An Intelligent System Approach to the Dynamic Hybrid Robot Control

    An Intelligent System Approach to the Dynamic Hybrid Robot Control by Md. Yeasin, Md. Mahmud Hasan

    Published 1996
    “…A one-pass smoothing algorithm was used to generate a practical smooth trajectory path in near real time. …”
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  2. 2
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  3. 3
    Performance Comparison Of Intelligent Tuning Methods Using Pid-Afcga And Pid-Afcpso In Attenuating The Vibration Of The Suspended Handle Model

    Performance Comparison Of Intelligent Tuning Methods Using Pid-Afcga And Pid-Afcpso In Attenuating The Vibration Of The Suspended Handle Model by Choo, Kinn

    Published 2021
    “…However, AFC requires proper tuning process to optimally attenuate the vibration. Thus, several tuning methods such as crude approximation (CA), genetic algorithm (GA) and particle swarm optimization (PSO) are implemented and compared based on the performance of the suspended handle model under different vibration. …”
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  4. 4
    Real time self-calibration algorithm of pressure sensor for robotic hand glove system

    Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

    Published 2019
    “…The traditional calibration process for FlexiForce sensor used is a time-consuming task because it is usually done through manual and repetitive identification [1, 2]. …”
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  5. 5
    Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel

    Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel by Zamri, Ruzaidi

    Published 2016
    “…Second part is to obtain the optimum polishing parameter by using artificial intelligence technique which is able to predict the grit size, polishing time and polishing force parameter to remove the scratch by polishing process. …”
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  6. 6
    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets

    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

    Published 2021
    “…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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  7. 7
    Digital Transformation Using Industry 4.0 and Artificial Intelligence

    Digital Transformation Using Industry 4.0 and Artificial Intelligence by Keerthika M., Pragadeesh M., Santhiya M., Jebamalar G.B., Venu H.

    Published 2025
    “…Explainable artificial intelligence (XAI) conducts studies and creates tools, techniques, and algorithm designs that produce information and judgments made by AI-based systems that are comprehensible to humans. …”
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  8. 8
    Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters

    Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

    Published 2016
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  9. 9
    Gripping an object based on inspection of slip events for a robotic hand model

    Gripping an object based on inspection of slip events for a robotic hand model by Al-Shanoon, Abdulrahman Abdulkareem Sattoori, Ahmad, Siti Anom, Hassan, Mohd Khair

    Published 2017
    “…An effective grasping operation is required in intelligent robotic hands to address the well-known challenge that occurs during the gripping process. …”
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  10. 10
    Internet utility evaluation of a multi-start particle swarm optimization beamformer in a partial joint processing cellular network

    Internet utility evaluation of a multi-start particle swarm optimization beamformer in a partial joint processing cellular network by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

    Published 2016
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  11. 11
    Human evacuation movement simulation model: Concepts and techniques

    Human evacuation movement simulation model: Concepts and techniques by Noor Akma, Abu Bakar, Lim, Siew Mooi, Abdul Majid, Mazlina

    Published 2022
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  12. 12
    Human evacuation movement simulation model: Concepts and techniques

    Human evacuation movement simulation model: Concepts and techniques by Noor Akma, Abu Bakar, Lim, Siew Mooi, Abdul Majid, Mazlina

    Published 2022
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  13. 13
    Multistage quality control in manufacturing process using blockchain with machine learning technique

    Multistage quality control in manufacturing process using blockchain with machine learning technique by Gu, J., Zhao, L., Yue, X., Arshad, N.I., Mohamad, U.H.

    Published 2023
    “…The demand for predictive machine reliability and quality drives the development of intelligent manufacturing technologies. To this goal, a variety of machine learning algorithms are being studied. …”
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  14. 14
    Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm

    Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm by Mat Hussin, Ab Talib, Hanim, Mohd Yatim, Nik Mohd Ridzuan, Shaharuddin, Muhamad Sukri, Hadi, Intan Zaurah, Mat Darus, Annisa, Jamali

    Published 2020
    “…To overcome this problem, an intelligent optimization method known as firefly algorithm (FA) was used by this study to optimize the force tracking controller (FTC) parameters as to achieve the exact damping force of MR damper system. …”
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  15. 15
    Intelligent active force control of a robotic arm using genetic algorithm

    Intelligent active force control of a robotic arm using genetic algorithm by Mailah, Musa, Wong, Min Yee, Jamaluddin, Hishamuddin

    Published 2002
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  16. 16
    Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm

    Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm by Mailah, Musa

    Published 2000
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  17. 17
    An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery

    An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery by Wan Hasbullah, Mohd Isa, Zahari, Taha, Ismail, Mohd Khairuddin, Anwar, P. P. A. Majeed, Khairul Fikri, Muhammad, Ali, Mohammed A. H., Jamaluddin, Mahmud, Zulkifli, Mohamed

    Published 2016
    “…This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. …”
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  18. 18
    A hybrid intelligent active force controller for robot arms using evolutionary neural networks

    A hybrid intelligent active force controller for robot arms using evolutionary neural networks by Hussein, S.B, Jamaluddin, H, Mailah, M, Zalzala, A.M.S

    Published 2000
    “…In this paper, we propose a hybrid intelligent parameter estimator for the active force control (AFC) scheme which utilizes evolutionary computation (EC) and artificial neural networks (ANN) to control a rigid robot arm. …”
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  19. 19
    A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed

    A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed by Tengku Mohamed, Tengku Luqman

    Published 2016
    “…An intelligent Active Force Control (AFC) scheme is utilised to compensate disturbances that a conventional PID control algorithm alone is unable to due to the system’s highly nonlinear behaviour. …”
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  20. 20
    Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE)

    Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE) by Saiful Anuar, Abu Bakar, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba

    Published 2012
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