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  1. 1
    Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks

    Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks by Roslan, Nurfarah Arina

    Published 2022
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    Monograph
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  2. 2
    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim

    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim by Hamzah, Irni Hamiza, Ibrahim, Mohammad Nizam, Mohd Kasim, Linda

    Published 2006
    “…This project has developed a user-friendly pattern recognition system by using MATLAB GUI. …”
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    Research Reports
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  3. 3
    Extending the decomposition algorithm for support vector machines training

    Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

    Published 2003
    “…The decomposition algorithm developed by Osuna et al. (1997a) reduces the training cost to an acceptable level. …”
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  4. 4
    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing

    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
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  5. 5
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, S.Y., Yap, K.S., Yap, H.J., Tan, S.C.

    Published 2015
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  6. 6
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong S.Y., Yap K.S., Yap H.J., Tan S.C.

    Published 2023
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  7. 7
    Development of spike train algorithms for physiotherapy assessment using deep learning approaches

    Development of spike train algorithms for physiotherapy assessment using deep learning approaches by Nor Rashid, Fadilla' Atyka

    Published 2021
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    Thesis
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  8. 8
    Jawi recognition system

    Jawi recognition system by Nur Aziela, Mansor

    Published 2010
    “…To improve the recognition of the character, the system uses neural network training algorithm called Supervised Learning to receive new character pattern in order to strengthen the weight of the pixels. …”
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    Undergraduates Project Papers
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  9. 9
    Case study : an effect of noise in character recognition system using neural network

    Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

    Published 2003
    “…This projects uses the most popular training method in character recognition problem, namely backpropagation algorithm. …”
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    Thesis
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  10. 10
    Financial time series predicting using machine learning algorithms

    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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  11. 11
    Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks

    Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks by Abusnaina, Ahmed A. A.

    Published 2015
    “…The major objective of this thesis is to achieve better performance in terms of convergence training time and classification accuracy for pattern classification by proposing new supervised training methods for Artificial Neural Networks (ANN) based on the MWO algorithm. …”
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  12. 12
    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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  13. 13
    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection

    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection by Muhammad Arif, Mohamad, Muhammad Aliif, Ahmad, Zuriani, Mustaffa

    Published 2024
    “…There are multiple techniques in training the network, one of which is training with metaheuristic algorithms. …”
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  14. 14
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

    Published 2013
    “…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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  15. 15
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

    Published 2013
    “…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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  16. 16
    ECG peak recognition using Artificial Neural Network / Sharifah Saliha Syed Bahrom and Leong Jenn Hwai.

    ECG peak recognition using Artificial Neural Network / Sharifah Saliha Syed Bahrom and Leong Jenn Hwai. by Syed Bahrom, Sharifah Saliha, Leong, Jenn Hwai

    Published 2007
    “…It takes 50 epochs to learn a training data consisting of 782 samples. The MLP which has been trained with BR algorithm has given 88.94 % correct recognition from 977 independent test data. …”
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    Research Reports
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  17. 17
    Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim

    Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim by Ibrahim, Erman

    Published 2007
    “…This project is about recognizing hand gesture for sign language using backpropagation (BP) algorithm that is one of the training algorithms used in the Artificial Neural Network (ANN). …”
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  18. 18
    EMG motion pattern classification through design and optimization of neural network

    EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. …”
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    Proceeding Paper
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  19. 19
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…It extends classical set theory by incorporating into the set model the notion of classification as indiscernibility relation.In previous work rough sets approach application to the field of speech recognition was limited to the pattern matching stage. That is, to use training speech patterns to generate classification rules that can be used later to classify input words patterns. …”
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  20. 20
    Neural network paradigm for classification of defects on PCB

    Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

    Published 2003
    “…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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