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  1. 1
    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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  2. 2
    Machine learning application in predicting anterior cruciate ligament injury among basketball players

    Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

    Published 2025
    “…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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  3. 3
    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy

    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  4. 4
    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Predicting Reservoir Water Level

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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  5. 5
    Development Of Generative Computer-Aided Process Planning System For Lathe Machining

    Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

    Published 2019
    “…To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. …”
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  6. 6
    Active force control with iterative learning control algorithm for a vehicle suspension

    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. …”
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  7. 7
    A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant

    A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

    Published 2023
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  8. 8
    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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  9. 9
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  10. 10
    Open architecture pc-based CNC controller

    Open architecture pc-based CNC controller by Yusoff, Wan Azhar

    Published 2006
    “…The objectives of this project are two: developing CNC controller and developing a prototype machine to implement the controller. …”
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  11. 11
    Support directional shifting vector: A direction based machine learning classifier

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  12. 12
    Optimization machining parameters in pocket milling using genetic algorithm and mastercam

    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
    “…A fitness function of production time incorporated of roughing and finishing process has been developed in Matlab Software. …”
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  13. 13
    Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm

    Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm by Rosmazi, Rosli, Musa, Mailah, Priyandoko, Gigih

    Published 2014
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  14. 14
    To study the multi-objective optimization of EDM using genetic algorithm

    To study the multi-objective optimization of EDM using genetic algorithm by Fairuz, Idris

    Published 2013
    “…EDM is one of the most accurate manufacturing processes for creating geometric shapes whether complex or simple in parts and assemblies. Development of EDM process has resulted in significant improvements in operating techniques, productivity and accuracy, which the result of this machining development has helped variability in EDM process. …”
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  15. 15
    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms

    Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

    Published 2001
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  16. 16
    A comparative study of vibrational response based impact force localization and quantification using different types of neural networks / Wang Yanru

    A comparative study of vibrational response based impact force localization and quantification using different types of neural networks / Wang Yanru by Wang, Yanru

    Published 2018
    “…In the study, the effort to find better neural network algorithms in the application of impact force indetification continues. …”
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  17. 17
    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
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  18. 18
    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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  19. 19
    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm

    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

    Published 2023
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  20. 20
    Development of machine learning-based algorithm to determine the condition in transformer oil

    Development of machine learning-based algorithm to determine the condition in transformer oil by Mohsen Al-Katheri, Hussein Hasan

    Published 2021
    “…Machine Learning (ML) algorithm have been utilized to detect the fault more accurate. …”
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