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  1. 1

    Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

    Published 2023
    “…The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution…”
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    Thesis
  2. 2

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…They are Cross Entropy and also Genetic Algorithm. CE is a new algorithm that was recently developed using probability. …”
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  3. 3

    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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    Article
  4. 4

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. Also, convergence in the probability function of employee bees’ movement was prevented by increasing the number of route-creating tours. …”
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    The effect of job satisfaction on the relationship between organizational culture and organizational performance by Imran, Muhammad

    Published 2023
    “…The proposed algorithm is ranked first among the stated algorithms with respect to its performance in getting the optimal solution…”
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  8. 8

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…The purpose of this study is to observe the reliability of genetic algorithm in our previously simulated network optimization in a data centre. …”
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  9. 9

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…The purpose of this study is to observe the reliability of genetic algorithm in our previously simulated network optimization in a data centre. …”
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    Article
  10. 10

    Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

    Published 2015
    “…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. The optimal number of cluster for FCM is obtained through cluster validity analysis. …”
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    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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    Article
  13. 13

    Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors by Ehteram M., Afan H.A., Dianatikhah M., Ahmed A.N., Fai C.M., Hossain M.S., Allawi M.F., Elshafie A.

    Published 2023
    “…Climate models; Climatology; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Mean square error; Particle swarm optimization (PSO); Principal component analysis; Stream flow; Adaptive neuro-fuzzy inference system; ANFIS-PSO; Climate index; Confidence levels; ENSO; Probability spaces; Root mean square errors; Streamflow simulations; Fuzzy inference; assessment method; El Nino-Southern Oscillation; genetic algorithm; index method; model; prediction; seasonal variation; streamflow; uncertainty analysis…”
    Article
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  15. 15

    Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

    Published 2012
    “…The Genetic Algorithms (GAs) have been very successful in handling optimization problems which are difficult. …”
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  16. 16

    Rainfall modeling using two different neural networks improved by metaheuristic algorithms by Sammen S.S., Kisi O., Ehteram M., El-Shafie A., Al-Ansari N., Ghorbani M.A., Bhat S.A., Ahmed A.N., Shahid S.

    Published 2024
    “…Six hybrid soft computing models, including�multilayer perceptron (MLP)�Henry gas solubility optimization (HGSO), MLP�bat algorithm (MLP�BA), MLP�particle swarm optimization (MLP�PSO), radial basis neural network function (RBFNN)�HGSO, RBFNN�PSO, and RBFGNN�BA, were used in this study to forecast monthly rainfall at two stations in Malaysia (Sara and Banding). …”
    Article
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    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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  20. 20

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Thesis