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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
    “…For overall, the back-propagation algorithm has been proved as a method that can be used for recognition areas.…”
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  2. 2
    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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  3. 3
    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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  4. 4
    Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach

    Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach by Gholizadeh, Somayyeh

    Published 2018
    “…This approach tunes the parameters of the linear programming models that are used in the other algorithms by using a dynamic element. …”
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  5. 5
    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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  6. 6
    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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  7. 7
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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  8. 8
    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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    Proceeding Paper
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  9. 9
    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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    Monograph
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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
    “…It also explains on the filtering sequences used and results produced by the developed program.…”
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  11. 11
    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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    Final Year Project
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  12. 12
    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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  13. 13
    Parallel Block Methods for Solving Ordinary Differential Equations

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

    Published 2004
    “…Subsequently, a more structured and efficient algorithm comprising the block methods was constructed for solving systems of first order ODEs using variable step size and order. …”
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  14. 14
    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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  15. 15
    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
    “…Visual C++ object-oriented programming language was used to build the Intelligent Learning System for Turning. …”
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  16. 16
    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar

    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar by Vijyakumar, Kanendra Naidu

    Published 2015
    “…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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  17. 17
    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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  18. 18
    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. …”
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  19. 19
    Differentiating Agarwood Oil Quality Using Artificial Neural Network

    Differentiating Agarwood Oil Quality Using Artificial Neural Network by Saiful Nizam, Tajuddin, Nurlaila, Ismail, Nor Azah, Mohd Ali, Mailina, Jamil, Mohd Hezri, Fazalul Rahiman, Mohd Nasir, Taib

    Published 2013
    “…Back-propagation training algorithm and sigmoid transfer function were used to optimize the parameters in the training network. …”
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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 on-line stage, the ANN parameters, i.e. the weights and biases, are further trained using live data and back-propagation until a satisfactory result is obtained. …”
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