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  1. 1
    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu

    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

    Published 2005
    “…There are three main programs work together. The programs are back-propagation neural network program, training and performance program and recognition program. …”
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  2. 2
    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen

    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen by Panagen, Suriyanti

    Published 2006
    “…Knowledge appearance is compulsory for neural network in which it comes under the training phase before it recognize or detecting any pattern.A study about the artificial neural network has been done and back propagation training algorithm is suitable for this system development. …”
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  3. 3
    Back propagation neural network approach for churn prediction: a case study in Celcom (M) Berhad / Hapida Husin

    Back propagation neural network approach for churn prediction: a case study in Celcom (M) Berhad / Hapida Husin by Husin, Hapida

    Published 2008
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  4. 4
    Development of Path Loss Models for Smooth and Convex Surfaces Terrains in Malaysian Environment

    Development of Path Loss Models for Smooth and Convex Surfaces Terrains in Malaysian Environment by Wong, Peng Kiong

    Published 2004
    “…An integrated UPMPL path loss model for both smooth and convex surfaces terrains has been developed and implemented using Agilent VEE. The UPMPL program provides the utility for calculating the signal characteristics of radio propagation paths and is realized in the run time format version. …”
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  5. 5
    Invigilation timetabling system using genetic algorithm (GA) / Shahirah Mohamed Hatim

    Invigilation timetabling system using genetic algorithm (GA) / Shahirah Mohamed Hatim by Shahirah, Mohamed Hatim

    Published 2011
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  6. 6
    Backpropagation algorithm for rice yield prediction

    Backpropagation algorithm for rice yield prediction by Puteh, Saad, Mohamed Rizon, Mohamed Juhari, Nor Khairah, Jamaludin, Siti Sakira, Kamarudin, Aryati, Bakri, Nursalasawati, Rusli

    Published 2009
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  7. 7
    Finite element modelling of damage fracture and fretting fatigue

    Finite element modelling of damage fracture and fretting fatigue by Wahab, M. Abdel, Hilmy, Irfan, Hafiz, Tauqeer, Talemi, R. Hojjati

    Published 2012
    “…Furthermore, crack propagation algorithm is programmed within FE code using the principles of Fracture Mechanics and Paris law. …”
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  8. 8
    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub Md. Som

    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

    Published 2014
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  9. 9
    Poverty Classification of Central Perak Population Using Machine Learning

    Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

    Published 2019
    “…In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. …”
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  10. 10
    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms

    Automatic filtering of far outliers in multibeam echo sounding dataset using robust detection algorithms by Mahmud, Mohd. Razali, Mohd. Yusof, Othman

    Published 2005
    “…Thus, a post-processing program was developed to detect and discard the MBES far outliers based on behaviours of propagated beam in the multibeam sonar system. …”
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  11. 11
    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. ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. …”
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  12. 12
    Parallel Block Methods for Solving Ordinary Differential Equations

    Parallel Block Methods for Solving Ordinary Differential Equations by Abdul Majid, Zanariah

    Published 2004
    “…The parallel programs were run on a Sequent Symmetry SE30 parallel computer.The Cq stability in the multistep method was introduced and the focused was on the error propagation from a more practical angle. …”
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  13. 13
    Speed control of separately excited dc motor using artificial intelligent approach

    Speed control of separately excited dc motor using artificial intelligent approach by Bernard, Albinus

    Published 2013
    “…A neural network controller with learning technique based on back propagation algorithm is developed. These two neural are training by Levenberg�Marquardt. …”
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  14. 14
    Enhancing obfuscation technique for protecting source code against software reverse engineering

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  15. 15
    Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin

    Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin by Samsudin, Fahmi

    Published 2023
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  16. 16
    Monitoring and prediction of bearing failure by acoustic emission and neural network

    Monitoring and prediction of bearing failure by acoustic emission and neural network by Mahamad, Abd Kadir

    Published 2005
    “…An experimental rig was setup to collect data on bearing by using Machine Health Checker (MI-IC) Memo assist with MHC Analysis software. In the development of ANN modeling, the result obtained shows that the optimum model was Elman network with training algorithm. …”
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  17. 17
    Voltage tracking of a DC-DC buck converter using neural network control

    Voltage tracking of a DC-DC buck converter using neural network control by Mohamad Narsardin, Mohamad Adhar

    Published 2012
    “…In order to overcome this main problem, a neural network controller with online learning technique based on back propagation algorithm is developed. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. …”
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  18. 18
    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin

    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

    Published 2012
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  19. 19
    Academic Achievement Prediction Model Using Neural Networks

    Academic Achievement Prediction Model Using Neural Networks by Normaziah, Abdul Rahman

    Published 2002
    “…A neural network technique, using Multi Layer Perceptron (MLP) and back propagation algorithm was employed. A total of 248 data samples from Information Technology and Multimedia Diploma students were collected, trained and tested using this model. …”
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  20. 20
    Hybrid intelligent active force controller for robot arms using evolutionary neural networks

    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. The EC part of the algorithm composes of a hybrid genetic algorithm (GA) and an evolutionary program (EP). …”
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