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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
    “…Following the best selection of neural network algorithm, BR algorithm is further trained using 50-70% training with 10-28 hidden neurons. …”
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    Monograph
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  2. 2
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…Due to that, many algorithms employ different training algorithms to guide the network for providing an accurate result with less training and testing error. …”
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    Thesis
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  3. 3
    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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  4. 4
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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  5. 5
    E-Handrawn Calculator

    E-Handrawn Calculator by Mohamad, Syamimi

    Published 2008
    “…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
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    Final Year Project
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  6. 6
    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…On the whole, BR algorithm with 60% training and 30 hidden nodes were successfully developed for BOD analysis, meanwhile, 70% training for COD analysis with the regression values of 0.9978 and 0.9976 respectively. …”
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    Monograph
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  7. 7
    Logic Programming In Radial Basis Function Neural Networks

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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  8. 8
    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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  9. 9
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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  10. 10
    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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  11. 11
    Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets

    Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets by Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly

    Published 2014
    “…The ANN training data were obtained from Open-ended Coaxial Probe (OCP) microwave measurements and the quasi-static admittance model, the ANN was trained with four different training algorithms: Levenberg Marquardt (LM) algorithm, Gradient Descent with Momentum (GDM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA) algorithm. …”
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  12. 12
    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
    “…ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  13. 13
    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding

    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

    Published 2007
    “…Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques three different error back propagation algorithms have been developed for use in training two types of neural networks, a single hidden layer network and three hidden layers network. …”
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  14. 14
    Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction

    Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction by Heng S.Y., Ridwan W.M., Kumar P., Ahmed A.N., Fai C.M., Birima A.H., El-Shafie A.

    Published 2023
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  15. 15
    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks

    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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    Conference or Workshop Item
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  16. 16
    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks

    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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  17. 17
    Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization

    Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization by Wong, Yong Jie, Arumugasamy, Senthil Kumar, Jewaratnam, Jegalakshimi

    Published 2018
    “…A multilayer feedforward neural network (FFNN) model with 11 different training algorithms is developed for the multivariable nonlinear biopolymerization of polycaprolactone (PCL). …”
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  18. 18
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…Results show that the reinforced network classifier with GA feature selection algorithm has successfully increased the classification accuracy of training process and testing process by 13.87% and 14.21% respectively compared to the conventional neural network classifier. …”
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  19. 19
    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
    “….: CCD cameras, microphones and scanners) have fostered the development of pattern recognition algorithms in new application domains (i.e.: fuzzy logic, neural network and genetic algorithm). …”
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    Research Reports
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  20. 20
    Application Of Neural Network In Malaria Parasites Classification

    Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

    Published 2006
    “…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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