Search Results - (( variable learning modified algorithm ) OR ( evolution optimisation system algorithm ))

Refine Results
  1. 1
  2. 2

    Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

    Published 2023
    “…Electric power factor; Electric power transmission networks; Evolutionary algorithms; Optimization; Differential Evolution; Differential evolution algorithms; Distributed generation source; Multiple distributed generations; Optimal allocation; Optimisations; Power factorAbstract; Power system constraints; Distributed power generation; algorithm; distribution system; energy planning; operations technology; optimization…”
    Article
  3. 3

    Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

    Published 2014
    “…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    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. …”
    Get full text
    Get full text
    Thesis
  6. 6
  7. 7

    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.…”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    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. …”
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    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. …”
    Get full text
    Get full text
    Thesis
  10. 10

    iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

    Published 2024
    “…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14
  15. 15

    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. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16
  17. 17

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    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
  20. 20

    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.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Article