Search Results - (( developing learning function algorithm ) OR ( data validation using algorithm ))

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  1. 1

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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    Article
  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
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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    Thesis
  3. 3

    A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

    Published 2025
    “…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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    Thesis
  4. 4

    Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

    Published 2024
    “…In addition, the assessment using rs-fMRI data to classify ASD fails to attain the biomarker standards, and the obstacle still does not settle in the previous study. …”
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    Thesis
  5. 5

    E-Handrawn Calculator by Mohamad, Syamimi

    Published 2008
    “…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
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    Final Year Project
  6. 6

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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    Monograph
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    Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali by Mohd Adli , Md Ali

    Published 2017
    “…Thus, development of an SOM algorithm for high energy physics datasets was performed. …”
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    Thesis
  10. 10

    Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

    Published 2025
    “…Data annotation using semi-supervised learning which is self-training technique need to be accomplished as the dataset is unlabeled. …”
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    Article
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    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…The ability of wavelets for localization in both time and frequency domain will help OSELM to train the WN in both uniform and non-uniform data sets. Moreover, the ability of initialization the hidden nodes parameters using density function and recursive algorithm will help WN-OSELM to perform useful generalization facility and modeling accuracy. …”
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    Thesis
  13. 13

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…In order to further validate the position of the tagging in the pallet box of the Random Forest model developed, a different predefined location was used to validate the model. …”
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    Thesis
  14. 14

    Car dealership web application by Yap, Jheng Khin

    Published 2022
    “…Validations were conducted to prove the correctness of the transfer learning algorithm. …”
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    Final Year Project / Dissertation / Thesis
  15. 15

    Prediction of lattice constant of pyrochlore compounds using optimized machine learning model by Mohamad Zamri, Isma Uzayr, Abd Rahman, Mohd Amiruddin, Bundak, Caceja Elyca

    Published 2023
    “…Three different kernel functions were used in PSO-SVR (Linear, Polynomial, and RBF kernel) shows that PSO-SVR algorithm with RBF function had better accuracy than other kernel functions. …”
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    Article
  16. 16

    From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana by Gerhana, Yana Aditia

    Published 2025
    “…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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    Thesis
  17. 17

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Multilayer Feedforward Back Propagation (MLFFBP) was used. Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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    Thesis
  18. 18

    Identification Of Flow Blockage Levels In Centrifugal Pump By Machine Learning by Ng, Woon Li

    Published 2021
    “…Raw data are collected by using Siemens LMS SCADAS Mobile data acquisition system. …”
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    Monograph
  19. 19

    Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

    Published 2025
    “…This research presented a technique for projecting sales utilising current data through a machine learning algorithm. The CRISP-DM approach was employed to execute the project across the phases of business understanding, data preparation, modelling, assessment, and deployment. …”
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    Student Project
  20. 20

    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

    Published 2022
    “…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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    Monograph