Search Results - (( parameter optimization model algorithm ) OR ( data classification system algorithm ))

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  1. 1

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

    Published 2018
    “…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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    Undergraduates Project Papers
  2. 2

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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    Thesis
  3. 3

    Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs by Liew, W.S., Seera, M., Loo, C.K., Lim, E.

    Published 2015
    “…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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    Article
  4. 4

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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    Thesis
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    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

    Published 2025
    “…Optimizers play an essential role in adjusting the model’s parameters to minimize errors, assisting the learning process during the model development. …”
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    Proceeding Paper
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    Predicting heart disease using ant colony optimization / Siti Aisyah Ismail by Ismail, Siti Aisyah

    Published 2021
    “…Thus, this study used the Ant Colony Optimization algorithm with data mining called Ant-Miner to predict heart disease because it is said that Ant-Miner’s rule list is simpler than other rule induction algorithms. …”
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    Student Project
  10. 10

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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    Thesis
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    Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

    Published 2025
    “…Edited Nearest Neighbour with Manhattan distance measure, which demonstrated over 85.00% accuracy in previous studies, is assessed alongside Minkowski and Mahalanobis distances to achieve the best model. After parameter tuning of Random Forest, the Edited Nearest Neighbour-Manhattan-Random Forest model outperformed, achieving 90.77% accuracy and reducing data loss from 70.00% to 17.50%. …”
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    Thesis
  13. 13

    Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

    Published 2022
    “…We also scaled the features to standardize unconstrained features in data, available in a fixed range for better optimization of models. …”
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    Article
  14. 14

    Big data analytics and classification of cardiovascular disease using machine learning by Narejo, S., Shaikh, A., Memon, M.M., Mahar, K., Aleem, Z., Zardari, B.

    Published 2022
    “…We also scaled the features to standardize unconstrained features in data, available in a fixed range for better optimization of models. …”
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    Article
  15. 15

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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    Thesis
  16. 16

    Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

    Published 2018
    “…There was a need for efficient segmentation algorithm, optimization strategy, feature extraction and classification, and robust statistical and computational intelligence models to accomplish the set aims. …”
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    Thesis
  17. 17

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The intelligent algorithm ML-ADR fault classifier model could discriminate 10 different far-end short circuit fault types from two network topology changes with and without midpoint integrated STATCOM on the Matlab/Simulink power grid system model. …”
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    Thesis
  18. 18

    Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

    Published 2012
    “…To achieve this, other objectives were targeted such as, to design a multi-echelon supply chain for the NGTSCs, to develop Extended Genetic Algorithms (EGAs), for solving the model, and to validate the mathematical model with a real world case study in natural gas industry. …”
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    Thesis
  19. 19

    Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

    Published 2022
    “…The optimal relations among all the image parameters successfully explained the robustness of the partial least squares (PLS) models which demonstrated a good prediction performance of all quality attributes of pineapples with R2 values of up to 0.94. …”
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    Thesis
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    Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

    Published 2014
    “…Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. …”
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    Conference or Workshop Item