Search Results - (( parameter classifications using algorithm ) OR ( changes optimization bat algorithm ))

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  1. 1

    Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty by Ehteram, Mohammad, Mousavi, Sayed Farhad, Karami, Hojat, Farzin, Saeed, Singh, Vijay P., Chau, Kwok Wing, El-Shafie, Ahmed

    Published 2018
    “…A hybrid framework (optimization-climate change) was used for reservoir operation and the bat algorithm was used for minimization of irrigation deficit. …”
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    Article
  2. 2

    Optimal operation of hydropower reservoirs under climate change by Ehteram M., Ahmed A.N., Chow M.F., Latif S.D., Chau K.-W., Chong K.L., El-Shafie A.

    Published 2024
    “…The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. …”
    Article
  3. 3

    Optimal operation of hydropower reservoirs under climate change by Ehteram M., Ahmed A.N., Chow M.F., Latif S.D., Chau K.-W., Chong K.L., El-Shafie A.

    Published 2023
    “…The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. …”
    Article
  4. 4

    Frequency stabilization in interconnected power system using bat and harmony search algorithm with coordinated controllers by K., Peddakapu, M. R., Mohamed, P., Srinivasarao, P.K, Leung

    Published 2021
    “…To enhance the outcome of the proposed 2DOF–TIDN controller, its gain parameters are optimized with the use of a newly designed hybrid bat algorithm-harmony search algorithm (hybrid BA–HSA) technique. …”
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  5. 5

    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

    Published 2020
    “…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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    Article
  6. 6

    Assessment of energy storage and renewable energy sources-based two-area microgrid system using optimized fractional order controllers by Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Arya, Yogendra

    Published 2024
    “…Simulation results reveal that the AOA-based CFOID-FOPIDN outperforms other existing algorithms, such as particle swarm optimization (PSO), bat algorithm (BAT), moth flame optimization (MFO), and whale optimization algorithm (WOA). …”
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  7. 7

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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    Thesis
  8. 8

    Black widow optimization-based optimal PI-controlled wind turbine emulator by Premkumar K., Vishnupriya M., Babu T.S., Manikandan B.V., Thamizhselvan T., Ali A.N., Islam M.R., Kouzani A.Z., Parvez Mahmud M.A.

    Published 2023
    “…The performance of the BWOA optimized PI controller is compared with a BAT algorithm, particle swarm optimization, and genetic algorithm optimized PI controller to measure the effectiveness of the proposed control system. …”
    Article
  9. 9

    Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems by Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Licari, J.

    Published 2024
    “…The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. …”
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    Article
  10. 10

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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  11. 11

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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  12. 12

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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    Thesis
  13. 13

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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    Conference or Workshop Item
  14. 14

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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    Undergraduates Project Papers
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    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
    Conference Paper
  17. 17

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    Published 2019
    “…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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    Undergraduate Final Project Report
  18. 18

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    Published 2024
    “…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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    Article
  19. 19

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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    Thesis
  20. 20

    Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.] by Anang, N., Jailani, R., Mustafah, N., Manaf, H.

    Published 2018
    “…This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. …”
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    Article