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  1. 1
    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
    “…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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  2. 2
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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  3. 3
    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
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  4. 4
    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
    “…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. …”
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  5. 5
    SUDOKU HELPER

    SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

    Published 2015
    “…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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    Final Year Project
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  6. 6
    Investigating feed mix problem approaches: An overview and potential solution

    Investigating feed mix problem approaches: An overview and potential solution by Abd Rahman, Rosshairy, Chooi, Leng Ang, Ramli, Razamin

    Published 2010
    “…Feed is one of the factors which play an important role in determining a successful development of an aquaculture industry. …”
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  7. 7
    Optimization of robot plasma coating efficiency using genetic algorithm and neural networks / S.Prabhu and B.K.Vinayagam

    Optimization of robot plasma coating efficiency using genetic algorithm and neural networks / S.Prabhu and B.K.Vinayagam by S., Prabhu, B.K., Vinayagam

    Published 2017
    “…Using feed forward Artificial Neural Networks (ANNs) trained the experimental values with the Levenberg–Marquardt algorithm, the most influential of the factors were determined. …”
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  8. 8
    Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection

    Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection by Soong, Cai Juan

    Published 2023
    “…The main contribution of this research is the development of feed formulation using Evolutionary Algorithm (EA) with four variations of EA, which are Semi-Random Initialization – Binary Tournament Selection - EA (SR-BT-EA), Fibonacci Rabbit Initialization – Binary Tournament Selection - EA (FR-BT-EA), Semi-Random Initialization - Binary- Standard Deviation Tournament Selection - EA (SR-SD-EA) and Fibonacci Rabbit Initialization - Binary-Standard Deviation Tournament Selection - EA (FR-SD-EA). …”
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  9. 9
    Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari

    Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari by Ahmad Fakhri, Ab. Nasir

    Published 2011
    “…By using multi-cores environment, algorithm has to be changed in order to fully utilise the speed of the processors. …”
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  10. 10
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithms. …”
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  11. 11
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithm. …”
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  12. 12
    Multi objective optimisation for high speed end milling using simulated annealing algorithm

    Multi objective optimisation for high speed end milling using simulated annealing algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Shaffiar, Norhashimah, Seder, Amin M. F., Riza, Muhammad

    Published 2015
    “…The mathematical models have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response surface Methodology (RSM). …”
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  13. 13
    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm

    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm by Golshan, Abolfazl

    Published 2013
    “…Finally, non-dominated sorting genetic algorithm-II as evolutionary optimization approach was used for multi-objective optimization of the micro-end milling process. …”
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  14. 14
    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
    “…An Intelligent Learning System for the turning process was developed. Visual C++ object-oriented programming language was used to build the Intelligent Learning System for Turning. …”
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  15. 15
    A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation

    A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation by Abayomi, Olalere Olusegun, Ruth, Alara Oluwaseun, Bala, Mohamed Saad, Twibi, Mohamed Farag

    Published 2016
    “…The development of feed formulation is essentially a problem of optimization which involves selecting the best alternative, starting from a specified set of possibilities. …”
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  16. 16
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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  17. 17
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
    “…Results showed that robot controllers could be successfully developed using the POE-MOEA algorithm. The generated robot controllers allowed the robots to move towards to the light source even the simulation and testing environments are noticeably different.…”
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    Research Report
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  18. 18
    Energy cost optimization in high speed hard turning using simulated annealing algorithm

    Energy cost optimization in high speed hard turning using simulated annealing algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Hassan, Muhammad Hasibul, Shaffiar, Norhashimah

    Published 2015
    “…Regression models have been developed by using Box-Behnken design as a design of experiment. …”
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  19. 19
    Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models

    Enhancing riverine load prediction of anthropogenic pollutants: Harnessing the potential of feed-forward backpropagation (FFBP) artificial neural network (ANN) models by Khairudin K., Ul-Saufie A.Z., Senin S.F., Zainudin Z., Rashid A.M., Abu Bakar N.F., Anas Abd Wahid M.Z., Azha S.F., Abd-Wahab F., Wang L., Sahar F.N., Osman M.S.

    Published 2025
    “…The feed-forward neural network model with a backpropagation algorithm and Bayesian regularisation training algorithm outperformed the radial basis neural network. …”
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  20. 20
    Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algorithm technique

    Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algor... by Saidina Amin, Nor Aishah, Istadi, Istadi

    Published 2007
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