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  1. 1

    Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication by JAM'AAH, SUUD

    Published 2021
    “…The Particle Swarm Optimization (PSO) search method is adopted to search the optimized scaling factor to obtain optimal error rate performance. …”
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    Thesis
  2. 2

    Optimization of super twisting sliding mode control gains using Taguchi method by Jamaludin, Zamberi, Chiew, Tsung Heng, Bani Hashim, Ahmad Yusairi, Rafan, Nur Aidawaty, Abdullah, Lokman

    Published 2018
    “…This paper focuses on optimization of super twisting controller gains using Taguchi method with objective to minimize tracking error and the chattering effect. …”
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    Article
  3. 3

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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    Monograph
  4. 4

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
  5. 5

    Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

    Published 2023
    “…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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    Article
  6. 6

    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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  7. 7
  8. 8

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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    Thesis
  9. 9

    Disparity map algorithm for stereo matching process using local based method by Gan, Melvin Yeou Wei

    Published 2022
    “…Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. …”
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    Thesis
  10. 10

    Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

    Published 2024
    “…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. …”
    Article
  11. 11

    Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

    Published 2018
    “…In addition, a simple procedure is proposed to determine the optimal solution and predict the correlation factor and the frequency of the damaged communication tower by using the particle swarm optimization (PSO) method. …”
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    Thesis
  12. 12

    Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines by Mohd Ashraf, Ahmad, Yoganathan, G., Muhammad Ikram, Mohd Rashid, Hao, Mok Ren, Mohd Zaidi, Mohd Tumari

    Published 2025
    “…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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    Article
  13. 13

    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

    Published 2022
    “…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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  14. 14

    An adaptive localization system using particle swarm optimization in a circular distribution form by Alhammadi, Abdulraqeb, Hashim, Fazirulhisyam, Fadlee, Mohd, Shami, Tareq M.

    Published 2016
    “…The simulation results show the proposed method using HPSO-TVAC variant achieves very low distance error of 0.19 meter.…”
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    Article
  15. 15

    Tuning of PID controller for a synchronous machine connected to a non-linear load by Kasilingam G., Pasupuleti J.

    Published 2023
    “…This paper proposes a method of determining the optimal proportional integral derivative (PID) controller parameters using the particle swarm optimization (PSO) technique. …”
    Article
  16. 16

    Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

    Published 2015
    “…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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    Article
  17. 17

    Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

    Published 2020
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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    Thesis
  18. 18

    The comparison study among optimization techniques in optimizing a distribution system state estimation by Hazim Imad, Hazim

    Published 2017
    “…The states of these systems are first estimated through centralized approach using the proposed algorithm to compare with weighted least squares technique. …”
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  19. 19

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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  20. 20

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…PSO is a swarm-based search algorithm perform a stochastic search to explore the search space. …”
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    Thesis