Search Results - (( using simulation learning algorithm ) OR ( variable selection based algorithm ))

Search alternatives:

Refine Results
  1. 1
    Information Theoretic-based Feature Selection for Machine Learning

    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
    Save to List
    Saved in:
  2. 2
    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model

    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…The method of selection of the input variables, the number of rules, and the learning rate are briefly discussed. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    Random forest algorithm for co2 water alternating gas incremental recovery factor prediction

    Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

    Published 2020
    “…RF develops multiple decision trees based on the random selection of the input data and random selection of the variables. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    MCMAC–CVT: a novel on-line associative memory based CVT transmission control system

    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
    “…Extensive simulation results are presented to evaluate the control performance of a direct digital PID control algorithm with auto-tuning (Trans. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning

    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

    Published 2022
    “…Fifth, a novel agent selection algorithm was developed to enable the selection of the best agent and avoid under-fitting and over-fitting. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application

    Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

    Published 2023
    Article
    Save to List
    Saved in:
  9. 9
    Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering

    Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering by Annisa Eka Haryati, ., Sugiyarto, Surono, Tommy Tanu, Wijaya, Goh, Khang Wen, Aris, Thobirin

    Published 2022
    “…It simulated and processed using Fuzzy Subtractive Clustering Algorithm, Jupyter Notebook Software with Python programming language. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
    Get full text
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  12. 12
    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

    Published 2001
    “…Data containing eleven predictive variables was used to train and test neural network model. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks

    A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohd Shawal, Jadin

    Published 2023
    “…This study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor

    Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor by Mamat, Nor Hana, Mohd Noor, Samsul Bahari, Che Soh, Azura, Taip, Farah Saleena, Ab Rashid, Ahmad Hazri, Jufika Ahmad, Nur Liyana, Mohd Yusuff, Ishak

    Published 2017
    “…Thus it is beneficial to model the relationship of DO concentration with these variables based on real process data for further use in controller design. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  15. 15
    Development of robust procedures for partial least square regression with application to near infrared spectral data

    Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

    Published 2021
    “…To fill-in the gap in the literature, a new robust procedure in wavelength selection based on input scaling method is developed using Filter-Wrapper method. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…The variable block matching developed based on four stages which is the video and frame selection, threshold calculation, block size selection and search pattern. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Vehicular traffic noise prediction and propagation modelling using artificial neural network

    Vehicular traffic noise prediction and propagation modelling using artificial neural network by Ahmed, Ahmed Abdulkareem

    Published 2018
    “…The learning rate of 0.05 and a momentum of 0.9 were used in this experiment. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
    Conference paper
    Save to List
    Saved in:
  19. 19
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: