Search Results - (( developing function learning algorithm ) OR ( learning implications _ 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 study contributes insights into the importance of pre-processing and feature selection in improving algorithm performance. The findings have implications for developing accurate predictive models and improving diabetes detection.…”
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    Article
  2. 2

    The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater by Ghumman, A.S.M., Shamsuddin, R., Abbasi, A., Ahmad, M., Yoshida, Y., Sami, A., Almohamadi, H.

    Published 2024
    “…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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    Article
  3. 3

    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

    Published 2023
    “…The former is a parametric regression model providing functional models with direct interpretability. The latter is a machine learning non-parametric algorithm, more tolerant than other approaches in its assumptions, which has often been shown to outperform parametric algorithms. …”
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  4. 4

    HandGestureSense: Hand gesture recognition-controlled smart home automation by Tan, Teck Sheng

    Published 2024
    “…Through extensive training and fine-tuning using machine learning techniques, the system learns to recognize a series of gestures, each corresponding to a different command or function in a smart home environment. …”
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    Final Year Project / Dissertation / Thesis
  5. 5

    HandGestureSense: Hand gesture recognition-controlled smart home automation by Tan, Teck Sheng

    Published 2024
    “…Through extensive training and fine-tuning using machine learning techniques, the system learns to recognize a series of gestures, each corresponding to a different command or function in a smart home environment. …”
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    Final Year Project / Dissertation / Thesis
  6. 6

    Enhanced foreign exchange volatility forecasting using CEEMDAN with optuna-optimized ensemble deep learning model by Kausar, Rehan, Iqbal, Farhat, Raziq, Abdul, Sheikh, Naveed, Rehman, Abdul

    Published 2024
    “…Furthermore, the hyperparameters for the DL models are optimized using the Optuna algorithm. Finally, a hybrid ensemble model for forecasting exchange rate volatility is developed by combining the predictions of three distinct DL models. …”
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  7. 7

    Heart-design nexus: the emotion algorithm by Mohd Lokman, Anitawati

    Published 2025
    “…This book, "Heart-Design Nexus: The Emotion Algorithm", represents both a culmination and a continuation of that journey. …”
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    Book
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    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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    Thesis
  10. 10

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
    Article
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    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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    Thesis
  13. 13

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  14. 14

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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    Thesis
  15. 15

    E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan by Mohd Ridzuan, Nur Hafizah

    Published 2020
    “…The objective of the project is to design and develop an E-History Malaysian secondary school textbook system using Term Frequency-Inverse Document Frequency (TF-IDF) algorithm with text visualization and also to test the functionality and usability of the system through a web-based system. …”
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    Thesis
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    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…A transfer function simulation model is developed by using the MATLAB software. …”
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    Thesis
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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    Thesis
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    Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm by Zainuddin, Zarita

    Published 2001
    “…In this thesis, factors that govern the learning speed of the backpropagation algorithm are investigated and mathematically analyzed in order to develop strategies to improve the performance of this neural network learning algorithm. …”
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    Thesis