Search Results - optimal ((((((bee algorithm) OR (tree algorithm))) OR (svm algorithm))) OR (cell algorithm))*

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  1. 1
    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
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  2. 2
    Using the bees algorithm to optimise a support vector machine for wood defect classification

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
    “…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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  3. 3
    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer

    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

    Published 2023
    “…This algorithm named JAABC5ROC is the enhancement of Artificial Bee Colony (ABC) variant, JA-ABC5 by combining with Rate of Change (ROC)\. …”
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  4. 4
    Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem

    Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem by AlMahasneh, Hossam Sayel

    Published 2010
    “…Results show that there are different factors of GA that it is not exist in the Bees Algorithm. Both of the proposed algorithm finds optimal or near optimal solutions for the MACL especially in large problems.…”
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  5. 5
    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
    “…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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  6. 6
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Rahim At Samsuddin, H. A., Ab. Rahman, A. A. H., Andaljayalakshmi, G., Ahmad, R. B.

    Published 2008
    “…A binary tree method for non-slicing tree construction process is utilized for the placement and area optimization of macro-cell layout in very large scaled integrated (VLSI) design. …”
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  7. 7
    Intrusion Detection Systems, Issues, Challenges, and Needs

    Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

    Published 2021
    “…Optimization algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) algorithm , ant colony algorithm, and many other algorithms are used along with classifiers to improve the work of these classifiers in detecting intrusion and to increase the performance of these classifiers. …”
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  8. 8
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Hasliza, A. Rahim@Samsuddin, Ab Al-Hadi, Ab Rahman, Andaljayalakshmi, G., R. Badlishah, Ahmad, Wan Nur Suryani Firuz, Wan Arrifin

    Published 2009
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  9. 9
    Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree

    Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree by Hasliza, A. Rahim@Samsuddin, Ab Al-Hadi, Ab Rahman, R. Badlishah, Ahmad, 'Aini Syuhada, Md Zain, M.I., Ahmad, Wan Nur Suryani Firuz, Wan Arrifin

    Published 2009
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  10. 10
    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets

    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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  11. 11
    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree

    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Hasliza, A. Rahim@Samsuddin, Ab Rahman, A. A H, Andaljayalakshmi, G., R. Badlishah, Ahmad, Wan Nur Suryani Firuz, Wan Ariffin

    Published 2009
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  12. 12
    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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  13. 13
    Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan

    Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan by Misnan, Azizi

    Published 1997
    “…A depth - first search algorithm is used to search for optimal chaining. Theorems on number of branches needed to be explored at each node of search tree are derived. …”
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  14. 14
    Decision tree-based approach for online management of PEM fuel cells for residential application

    Decision tree-based approach for online management of PEM fuel cells for residential application by Mohd Rusllim, Mohamed

    Published 2004
    “…In this research, a Decision Tree (DT) algorithm is employed to obtain the optimal, or quasioptimal, settings of the fuel cell online and in a general framework. …”
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  15. 15
    The performance study of two genetic algorithm approaches for VLSI Macro-Cell layout area optimization

    The performance study of two genetic algorithm approaches for VLSI Macro-Cell layout area optimization by Hasliza, A. Rahim@Samsuddin, Rahman, A. A A, R. Badlishah, Ahmad, Wan Nur Suryani Firuz, Wan Ariffin, Muhammad Imran, Ahmad

    Published 2009
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  16. 16
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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  17. 17
    Decision tree-based approach for online management of pem fuel cells for residential application

    Decision tree-based approach for online management of pem fuel cells for residential application by Mohamed, Mohd Rusllim

    Published 2004
    “…In this research, a Decision Tree (DT) algorithm was employed to obtain the optimal, or quasi-optimal, settings of the fuel cell online and in a general framework. …”
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  18. 18
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  19. 19
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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  20. 20
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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