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  1. 1

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…The rest sets of experiments carried out to evaluate the proposed algorithms. Precisely, the second set revealed that the proposed genetic medoid based algorithms with both DB and VRC fitness functions produced more accurate results compared with the genetic means based algorithms in terms of the Fscore. …”
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    Thesis
  2. 2

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…The performance of the method is evaluated based on the ability to reduce function value after each iteration, ability to attain the lowest function value when applied to solve the well-known zebra-strip problem. …”
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    Article
  3. 3

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Mohd Sharif, Zakaria, Mohammad Fadhil, Abas, Fatimah, Dg Jamil, Norhafidzah, Mohd Saad, Addie, Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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    Conference or Workshop Item
  4. 4

    A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa by Musa, Asmaa

    Published 2007
    “…A large nimiber of techniques, such as Neurofuzzy algorithm methods are used to produce an efficient and effective system. …”
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    Thesis
  5. 5

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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    Thesis
  6. 6

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…Subsequently, the THF modelling scheme can be incorporated into an established real time NLFXLMS algorithm termed THF-NLFXLMS algorithm. The developed THF-NLFXLMS algorithm is tested by means of simulation and implemented experimentally using FPGA-based real time controller for a nonlinear ANC application. …”
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  7. 7

    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…Although, fuzzy clustering algorithms such as fuzzy c-means provides an inherent mechanism for the clustering of overlapping structures (objects) but this potential of the fuzzy methods which comes from its fuzzy membership functions have not been utilized effectively. …”
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    Book Section
  8. 8

    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods by Zakaria, Mohd Sharif, Abas, Mohammad Fadhil, Dg Jamil, Fatimah, Mohd Saad, Norhafidzah, Hashim, Addie Irawan, Pebrianti, Dwi

    Published 2024
    “…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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    Proceeding Paper
  9. 9

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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    Thesis
  10. 10

    Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty by Rahimi, Iman, Tang, Sai Hong, Ahmadi, Abdollah, Ahmad, Siti Azfanizam, Lee, Lai Soon, Sharaf, Adel M.

    Published 2017
    “…In order to evaluate the proposed algorithm, some performance metrics including the number of Pareto points, mean ideal points, and maximum spread are used, then the t-test analysis is done which points out that there is a significant difference between aforementioned algorithms.…”
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    Article
  11. 11

    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

    Published 2024
    “…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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    Article
  12. 12

    Self-adaptive conjugate method for a robust and efficient performance measure approach for reliability-based design optimization by Keshtegar, Behrooz, Baharom, Shahrizan, El-Shafie, Ahmed

    Published 2018
    “…The advanced mean value and hybrid mean value methods are commonly used to evaluate the probabilistic constraint of reliability-based design optimization (RBDO) problems. …”
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    Article
  13. 13

    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2018
    “…The statistical analysis was used to evaluate the performance of the model based on the objective function which is the Mean Square Error (MSE). …”
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    Article
  14. 14

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
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  17. 17

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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    Conference or Workshop Item
  18. 18

    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2024
    “…The statisti-cal analysis was used to evaluate the performance of the model based on the objective function which is the Mean Square Error (MSE). …”
    Article
  19. 19

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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    Thesis
  20. 20

    Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani

    Published 2022
    “…An improvement on the spiral dynamic algorithm (SDA), this method uses a concept centered on opposition-based learning, which is used to evaluate the fitness of agents at the opposite location to the current solution. …”
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    Article