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  1. 1
    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity

    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity by Dehkordi, Sepehr Ghasemi

    Published 2014
    “…An effective solution to mitigate such nonlinearly distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. The controller compensates the nonlinearity using a model of the saturation effect represented by Scaled Error Function (SEF). …”
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  2. 2
    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network

    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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  3. 3
    All-pass filtered x least mean square algorithm for narrowband active noise control

    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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  4. 4
    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)

    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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  5. 5
    Real time nonlinear filtered-x lms algorithm for active noise control

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

    Published 2012
    “…The SEF has been extensively used to model the saturation nonlinearity. A major drawback of using the SEF function lies in its theoretical nature such that for a finite integration limit, the SEF become non-elementary integral and requires infinite series or numerical methods for evaluation. …”
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  6. 6
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    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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  7. 7
    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)

    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). …”
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  8. 8
    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh

    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh by Seef Saadi , Fiyadh

    Published 2019
    “…The NARX algorithm is used for the modelling of Hg2+ removal. …”
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  9. 9
    Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods

    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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  10. 10
    Harmony search-based robust optimal controller with prior defined structure

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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  11. 11
    Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction

    Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

    Published 2013
    “…The second experiment used proposed method to model a three input nonlinear function. …”
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  12. 12
    A Mobile Application For Stock Price Prediction

    A Mobile Application For Stock Price Prediction by Choy, Yi Tou

    Published 2021
    “…The evaluation methods were Root Mean Square Error and Mean Absolute Error. …”
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    Final Year Project / Dissertation / Thesis
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  13. 13
    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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  14. 14
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    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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  15. 15
    Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm

    Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

    Published 2017
    “…The application of artificial neural network (ANN) to generate the production model is used to improve the modelling accuracy. The model output optimisation by genetic algorithm (GA) produces higher biogas production compared to the optimisation using statistical methods. …”
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  16. 16
    Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj

    Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj by Bryan Raj , Peter Jabaraj

    Published 2023
    “…To ensure the performance of the developed method in obtaining the optimized solution, the method is evaluated on 11 test benchmark functions named Sphere, SumSquare, Zakharov, Rosenbrock, Step, Ackley, Griewank, Rastrigin, Schwefel 2.26, Michalewicz and Egg Crate. …”
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  17. 17
    A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm

    A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm by Azmin, Farah Ayuni

    Published 2017
    “…Genetic algorithm is a method which is easily transferred to the existing simulations and models. …”
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  18. 18
    Optimization of coded signals based on wavelet neural network

    Optimization of coded signals based on wavelet neural network by Ahmed, Mustafa Sami

    Published 2015
    “…When compared with other existing methods, WNN yields better PSR, low Mean Square Error (MSE), less noise, range resolution ability and Doppler shift performance than the previous and some traditional algorithms like auto correlation function (ACF) algorithm.…”
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  19. 19
    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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  20. 20
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…Next, the weighted and transformed features were used to train Linear Discriminant Function (LDA) and to evaluate the constructed rule. …”
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