Search Results - (( variable learning modified algorithm ) OR ( evolution optimization bat algorithm ))

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  1. 1

    Multi-Swarm bat algorithm by Taha A.M., Chen S.-D., Mustapha A.

    Published 2023
    “…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
    Article
  2. 2

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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  3. 3

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. …”
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  4. 4
  5. 5

    New approach for sugarcane disease recognition through visible and near-infrared spectroscopy and a modified wavelength selection method using machine learning models by Pauline Ong, Pauline Ong, Jinbao Jian, Jinbao Jian, Xiuhua Li, Xiuhua Li, Chengwu Zou, Chengwu Zou, Jianghua Yin, Jianghua Yin, Guodong Ma, odong Ma

    Published 2023
    “…These results outperformed those obtained by other wavelength selection approaches, including the selectivity ratio, variable importance in projection, and the baseline method of the flower pollination algorithm.…”
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    Article
  6. 6

    Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz by Muhammad Firdaus , Aziz

    Published 2022
    “…The purpose of this study is to use machine learning (ML) and deep learning (DL) algorithms to predict and identify variables linked to short and long-term mortality in Asian STEMI and NSTEMI/UA patients and to compare these results to a conventional risk score. …”
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  7. 7

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. …”
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  8. 8

    MCMAC–CVT: a novel on-line associative memory based CVT transmission control system by Kai, Keng Ang, Quek, Chai, Abdul Rahman, Abdul Wahab

    Published 2002
    “…Engng, 10 (1996) 135) with momentum, neighborhood learning and Averaged Trapezoidal Output (MCMAC-ATO) as the neural control algorithm for controlling the CVT. …”
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  9. 9

    Feature selection for high dimensional data: An evolutionary filter approach. by Yahya, Anwar Ali, Osman, Addin, Ramli, Abdul Rahman, Balola, Adlan

    Published 2011
    “…The proposed approach is based essentially on a variable length representation scheme and a set of modified and proposed genetic operators. …”
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  10. 10
  11. 11

    Predicting motorcycle customization preferences using machine learning by Saputra, Ananta, Utoro, Rio Korio, Roedavan, Rickman, Soegiarto, Duddy, Moorthy, Kohbalan, Pratondo, Agus

    Published 2025
    “…This study explores potential by examining individual tendencies in choosing between modified and factory-original motorcycle. A dataset comprising 292 respondents was compiled, capturing variables such as age, social environment, financial capacity, and exposure to automotive communities and content. …”
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  12. 12
  13. 13

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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  14. 14

    Boosting and bagging classification for computer science journal by Wibawa, Aji Prasetya, Putri, Nastiti Susetyo Fanany, Al Rasyid, Harits, Nafalski, Andrew, Hashim, Ummi Rabaah

    Published 2023
    “…In the DT algorithm, both variables are altered, whereas, in the GNB algorithm, just the estimator's value is modified. …”
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  15. 15

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

    Published 2025
    “…The novelty of the approach recommended stems from the accuracy attained by modifying hyper-parameters with AO that has been paired with the fast processing speed of ELM. ? …”
    Article
  16. 16

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

    Published 2024
    “…The novelty of the approach recommended stems from the accuracy attained by modifying hyper-parameters with AO that has been paired with the fast processing speed of ELM.…”
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    Article
  17. 17

    Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

    Published 2018
    “…In this thesis, the human handwritten signature is introduced as a novel cover media (c) in conjunction with a steganography algorithm since there is a level of variability (i.e intra-user variability) within handwritten signature samples of an individual. …”
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    Thesis
  18. 18

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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    Thesis