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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
    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm

    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm by Mimi Muzlina, Mukri

    Published 2024
    “…The genetic algorithm is used in this optimization because it is capable of searching for global optimal solutions since the configuration of the method can be very flexible, allowing it to be used for a variety of problems. …”
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  3. 3
    Optimization of turning parameters using genetic algorithm method

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

    Published 2008
    “…This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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  4. 4
    Optimization of turning parameters using ant colony optimization

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…Method used for this project is Ant Colony Optimization. …”
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  5. 5
    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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  6. 6
    Machining optimization using Firefly Algorithm / Farhan Md Jasni

    Machining optimization using Firefly Algorithm / Farhan Md Jasni by Md Jasni, Farhan

    Published 2020
    “…For this project, we will verify the Firefly Algorithm (FA) into finding total profit rate by optimizing the machining parameter of milling operation and compare the effectiveness of FA with other non¬conventional method. …”
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  7. 7
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…This method was demonstrated for the optimization of machining parameters for milling operation. …”
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  8. 8
    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
    “…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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  9. 9
    Optimization machining parameters in pocket milling using genetic algorithm and mastercam

    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
    “…Mastercam software has been used to verify the algorithm's results by applying the optimum parameter generated by GA in the Mastercam. …”
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  10. 10
    Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm

    Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm by Mimi Muzlina, Mukri, Nor Atiqah, Zolpakar

    Published 2023
    “…The parameters involve during this optimization are cutting speed, feed rate, depth of cut and nose radius by using genetic algorithm optimization. …”
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  11. 11
    Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm

    Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm by Al Hazza, Muataz, Adesta, Erry Yulian Triblas, Superianto, M. Y., Riza, Muhammad

    Published 2012
    “…The mathematical models for the cutting temperature and surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). …”
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  12. 12
    Optimization of cutting parameters to minimize tooling cost in high speed turning of SS304 using coated carbide tool using genetic algorithm method

    Optimization of cutting parameters to minimize tooling cost in high speed turning of SS304 using coated carbide tool using genetic algorithm method by Al Hazza, Muataz Hazza Faizi, Mohmad Bakhari, Nur Amirah Najwa

    Published 2016
    “…The aim of this paper is to determine experimentally the optimum cutting levels that minimize the tooling cost in machining AISI 304 as a work piece machined by a coated carbide tool using one of the non-conventional methods: Genetic Algorithm (GA). …”
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  13. 13
    Surface roughness optimization in end milling using the multi objective genetic algorithm approach

    Surface roughness optimization in end milling using the multi objective genetic algorithm approach by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Riza, Muhammad, Mohammad Yuhan, Suprianto

    Published 2012
    “…The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). …”
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  14. 14
    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
    “…This paper presents the optimization of machining parameters in end milling processes by using the simulated annealing algorithm (SAA) as one of the unconventional methods in optimization. …”
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  15. 15
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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  16. 16
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  17. 17
    Experimental Investigation and Optimization of Minimum Quantity Lubrication for Machining of AA6061-T6

    Experimental Investigation and Optimization of Minimum Quantity Lubrication for Machining of AA6061-T6 by Najihah, Mohamed, M. M., Rahman, K., Kadirgama

    Published 2015
    “…Optimization is performed using a genetic algorithm and the optimized designs are obtained in the form of Pareto optimal designs. …”
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  18. 18
    Computational inteligence in optimization of machining operation parameters of ST-37 steel

    Computational inteligence in optimization of machining operation parameters of ST-37 steel by Golshan, Abolfazl, Ghodsiyeh, Danial, Gohari, Soheil, Ayob, Amran, Baharudin, B. T. Hang Tuah

    Published 2013
    “…In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. …”
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  19. 19
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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  20. 20
    Predictive modelling of machining parameters of S45C mild steel

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…The effects of cutting parameters on performance characteristics are studied using the signal-to-noise (S/N) ratio method. …”
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