Search Results - ((exraction algorithm) OR (((generation algorithm) OR (selection algorithm))))

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  1. 1
    Hybrid subjective evaluation of rule Exraction Algorithm using Weighted Subsethood-Based (WSBA)

    Hybrid subjective evaluation of rule Exraction Algorithm using Weighted Subsethood-Based (WSBA) by Othman, Mahmod, Ku-Mahamud, Ku Ruhana, Hawani, Shezrin, Hamzah, Amir, Khalid, Shaiful Annuar, Abdullah, Fader

    Published 2013
    “…Fuzzy rules are important elements that being highlighted in any fuzzy expert system.This research proposes the framework of subjective performance evaluation using fuzzy technique for ranking the performance of the financial performance of a company under a multi criteria environment.There are a lot of techniques used such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted.The framework is based on fuzzy multi-criteria decision-making that consists of fuzzy rules.The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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  2. 2
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  3. 3
    Automated path testing using the negative selection algorithm

    Automated path testing using the negative selection algorithm by Shayma Mustafa Mohi-Aldeen, Radziah Mohamad, Safaai Deris

    Published 2017
    “…Negative selection algorithm (NSA) has been used in this paper to generate test data for path testing automatically. …”
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  4. 4
    An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection

    An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection by Md Badarudin, Ismadi, Md Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mamat, Ali, Tengku Muda Mohamed, Mahmud

    Published 2012
    “…This paper presents the design of algorithm solution for selecting a planting lining technique. …”
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  5. 5
    Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization

    Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization by Kamal Z., Zamli, Abdul Kader, ., Fakhrud Din, ., Alhadawi, Hussam S.

    Published 2021
    “…This paper introduces a new variant of a metaheuristic algorithm based on Tiki-Taka algorithm, called selective chaotic maps Tiki-Taka algorithm (SCMTTA). …”
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  6. 6
    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…Technically, BFOA has been applied as supplementary algorithm for optimizing weight, parameters for other classifier algorithms and selecting optimised features for other classifiers. …”
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  7. 7
    A novel clustering based genetic algorithm for route optimization

    A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

    Published 2016
    “…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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  8. 8
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this paper, a new algorithm incorporating broadening selection strategy in competitive constraint handling paradigm for finding the optimum solution in constrained problems has been proposed, referred as Broadening Selection Competitive Constraint Handling (BSCCH). …”
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  9. 9
    A novel Bezier curve control point search algorithm for autonomous navigation using N-order polynomial search with boundary conditions

    A novel Bezier curve control point search algorithm for autonomous navigation using N-order polynomial search with boundary conditions by Sajith, Akhil Vinayak, Zakaria, M. A., Baarath, K., Anwar, P. P. Abdul Majeed

    Published 2021
    “…This method is able to generate the desired Bezier curve through the selected points. …”
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  10. 10
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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  11. 11
    Comparison between Genetic Algorithm and Prey-Predator Algorithm.

    Comparison between Genetic Algorithm and Prey-Predator Algorithm. by Ong, Hong Choon

    “…We also compared the performance of this algorithm with the genetic algorithm on selected test problems and we showed that the new algorithm performed better in our publication.…”
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  12. 12
    Selection, generation and extraction of MCCTree using XMCCTree

    Selection, generation and extraction of MCCTree using XMCCTree by Sazaly, Ummu Sulaim, Selamat, Mohd Hasan, Baharom, Salmi, A. Jabar, Marzanah

    Published 2012
    “…The algorithms transform the XML tree into a compact global tree called CGTree, and select the MCCTree from the CGTree. …”
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  13. 13
    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. …”
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  14. 14
    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…Individuals for the next generation are selected by using the objective function. …”
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  15. 15
    Wind power forecasting with metaheuristic-based feature selection and neural networks

    Wind power forecasting with metaheuristic-based feature selection and neural networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohammad Fadhil, Abas

    Published 2024
    “…This study proposes an innovative approach to enhance wind power generation forecasting accuracy by leveraging the strengths of metaheuristic algorithms for feature selection and integrating them with Neural Networks (NN). …”
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  16. 16
    Q-learning whale optimization algorithm for test suite generation with constraints support

    Q-learning whale optimization algorithm for test suite generation with constraints support by Hassan, Ali Abdullah, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

    Published 2023
    “…Experimental results for constraints combinatorial test generation demonstrate that the proposed QWOA-EMC outperforms WOA and performs competitively against other metaheuristic algorithms.…”
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  17. 17
    Comparative Study between Flower Pollination Algorithm and Cuckoo Search Algorithm for t-way Test Data Generation

    Comparative Study between Flower Pollination Algorithm and Cuckoo Search Algorithm for t-way Test Data Generation by Abdullah, Nasser, Kamal Z., Zamli

    Published 2018
    “…This paper presents a comparative study between two meta-heuristic strategies for t-way test data generation: Flower Pollination Algorithm (FPA) and Cuckoo Search (CS). …”
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  18. 18
    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…Optimization algorithms are successfully applied in the feature selection task in many systems. …”
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  19. 19
    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…Performance of each algorithm is compared in terms of number of test cases generated as well as the run time required. …”
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  20. 20
    An evaluation of feature selection technique for dendrite cell algorithm

    An evaluation of feature selection technique for dendrite cell algorithm by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

    Published 2014
    “…From the experiment, the Rough Set Genetic Algorithm reduct is found to be the most effect feature selection for dendrite cell algorithm when it generates a consistent result for all evaluation metrics. …”
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