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  1. 1

    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
  2. 2
  3. 3

    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
    “…Metaheuristic algorithms that aim to develop more effective hybrid algorithms by combining the good and successful aspects of more than one algorithm are algorithms inspired by nature. …”
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    Article
  4. 4

    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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    Article
  5. 5

    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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    Article
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  7. 7

    Development of classification algorithms of human gait by Koh, Chee Hong

    Published 2022
    “…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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    Final Year Project / Dissertation / Thesis
  8. 8

    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
    “…Despite the fact that ANN has been developing rapidly for many years, there are still some challenges concerning the development of an ANN model that performs effectively for the problem at hand. …”
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    Thesis
  9. 9

    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
  10. 10

    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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    Conference or Workshop Item
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    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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    Article
  13. 13

    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

    Published 2013
    “…In this study, sentiment classifier using clonal algorithm selection was developed to categorize sentiment in Malay newspaper (Berita Harian). …”
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    Thesis
  14. 14

    REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION by P ISKANDAR, YULITA HANUM

    Published 2006
    “…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
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    Thesis
  15. 15

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…Once training samples for each class are collected, the training statistics for each class and band are extracted to select those bands, which are most effective in discriminating each class of information from all others for classification. …”
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    Thesis
  16. 16

    Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

    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
  17. 17

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

    Published 2004
    “…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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    Thesis
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    Optimization of Feeder Bus Routes for Electric Train Service using Ant Colony Algorithm by Yung, Dellon Tan Tzet

    Published 2014
    “…One of the most effective and efficient mode of transportation in Malaysia would be the Electric Train Service (ETS). …”
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    Final Year Project
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    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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    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

    Published 2024
    “…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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    Thesis