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  1. 1
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
    Conference paper
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  2. 2
    Logic Programming In Radial Basis Function Neural Networks

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…The first technique is to encode the logic programming in radial basis function neural networks. …”
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  3. 3
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…The co-gasification process was modeled using SVM regression incorporated with linear, quadratic, and cubic kernel functions, GPR incorporated with rotational, squared, Matern 5/2, and exponential kernel functions, and non-linear response quadratic model (NLRQM) using sequential quadratic programming (SQP), and Levenberg-Marquardt (LM). …”
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  4. 4
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

    Published 2023
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  5. 5
    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…The co-gasification process was modeled using SVM regression incorporated with linear, quadratic, and cubic kernel functions, GPR incorporated with rotational, squared, Matern 5/2, and exponential kernel functions, and non-linear response quadratic model (NLRQM) using sequential quadratic programming (SQP), and Levenberg-Marquardt (LM). …”
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  6. 6
    A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization

    A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization by Ean, Kate Nee Goh, Jeng, Feng Chin, Wei, Ping Loh, Chea, Ling Tan

    Published 2014
    “…A genetic algorithm model was created in the second stage to optimize capacity output. …”
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  7. 7
    Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman

    Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman by Othman, Eda Azuin

    Published 2014
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  8. 8
    Projecting image on non-planar surface with zero-th order geometric continuity using simple dual-linear function and manipulation of strict integer implementation in programming language

    Projecting image on non-planar surface with zero-th order geometric continuity using simple dual-linear function and manipulation of strict integer implementation in programming la... by Yusoff, Fakhrul Hazman, Azhar, Muhammad Amirul

    Published 2015
    “…Usage of a projection system to display large screen images is still relevant in the midst of LED-based display increasing popularity.This is due to that the system itself is a mature technology, reliable and cheaper than the LED counterpart.While various methods had addressed the projection problems on curve surface, projecting image on jagged like surface (zero order geometric continuity) has yet to be studied in depth.This paper proposes a method for projecting image on non-planar surface with zero-order geometric continuity property using parametric modeling.The method manipulate linear function by combining two functions into one by taking advantage of computer programs strict implementation of integer variables.The method was applied to grid-based texturing algorithm in order to create the desired zero-continuity effect on the surface.The method was compared with texturing that implement existing curve algorithm to project image on the screen.Visual evaluation results showed that the proposed method fared better compared to existing curve-based projection algorithm.…”
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  9. 9
    Some metaheuristic algorithms for solving multiple cross-functional team selection problems

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
    “…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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  10. 10
    Software for modelling the static and dynamic flux linkage - current characteristics of A 6/4 SRM

    Software for modelling the static and dynamic flux linkage - current characteristics of A 6/4 SRM by Hashim, Mohd Nasir

    Published 1996
    “…Program in C language was developed to validate the algorithm provided by Torrey [5,7].…”
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  11. 11
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  12. 12
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  13. 13
    Implementation of repetitive control algorithm in reducing vibration using MATLAB/SIMULINK / Mohamad Zuhairy Mohamed

    Implementation of repetitive control algorithm in reducing vibration using MATLAB/SIMULINK / Mohamad Zuhairy Mohamed by Mohamed, Mohamad Zuhairy

    Published 2008
    “…As a new result it is in fact shown that the algorithm iteratively solves a Model Predictive Control related cost function. …”
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  14. 14
    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization

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

    Published 2022
    “…Integration of global search algorithm into ANN model further improved the model performance. …”
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  15. 15
    Explicit solution of parameter estimate using multiparametric programming for boost converter

    Explicit solution of parameter estimate using multiparametric programming for boost converter by Mid, E.C., Mukhtar, N.M., Syed Yunus, S.H., Abdul Hadi, Dayanasari, Ruslan, Eliyana

    Published 2023
    “…This work proposes an approach to estimate the parameters of capacitance and inductance in a boost converter using an explicit solution. A multiparametric programming (MPP) algorithm is fundamental to the suggested methodology, which aims to develop parameters as explicit functions of measurements. …”
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  16. 16
    Real-time algorithmic music composition application.

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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    Final Year Project / Dissertation / Thesis
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  17. 17
    A comparative study between univariate and bivariate time series models for crude palm oil industry in peninsular Malaysia / Pauline Jin Wee Mah and Nur Nadhirah Nanyan

    A comparative study between univariate and bivariate time series models for crude palm oil industry in peninsular Malaysia / Pauline Jin Wee Mah and Nur Nadhirah Nanyan by Wee Mah, Pauline Jin, Nanyan, Nur Nadhirah

    Published 2020
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  18. 18
    Adaptive and cooperative harmony search models for RNA secondary structure prediction

    Adaptive and cooperative harmony search models for RNA secondary structure prediction by Mohsen, Abdulqader Mohammed A.

    Published 2011
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  19. 19
    Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm

    Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Fai C.M., Afan H.A., Sapitang M., El-Shafie A.

    Published 2023
    “…The MLP�WA model was the best model among all. For the test stage, the mean absolute error of the MLP�WA model decreased to 30% and from 31 to 38% as compared to the radial basis function�whale algorithm (RBF�WA) and GP models, respectively. …”
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  20. 20
    Urban connected vehicle lane planning based on improved Frank Wolfe algorithm

    Urban connected vehicle lane planning based on improved Frank Wolfe algorithm by Anqi, Jiang, Faziawati, Abdul Aziz, Norsidah, Ujang, Mohd Afzan, Mohamed

    Published 2025
    “…First, a lane planning for urban connected vehicles bi-level programming model is constructed. Then, the upper-level model is solved using improved whale optimization, and the lower-level model is solved using improved Frank-Wolfe algorithm. …”
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