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  1. 1

    Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring by Ab Halim, Haizum Hanim

    Published 2021
    “…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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    Thesis
  2. 2

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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    Thesis
  3. 3

    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…This thesis steps towards developing a networked game, Literati game system that supporting two players at one time. …”
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    Thesis
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    Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

    Published 2006
    “…A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. The Gibbs sampler algorithm is applied using the WinBUGS programming package. …”
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    Thesis
  10. 10

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Thesis
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    Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

    Published 2015
    “…Modeling Computational Problem Solving (CPS) is the main issue in teaching programming where the given text is needed to be transformed into a model then later into a programming language. …”
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    Thesis
  13. 13

    Enhanced dynamic security assessment for power system under normal and fake tripping contingencies. by A. Salih, Qusay

    Published 2019
    “…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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    Thesis
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    Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

    Published 2024
    “…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. …”
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    Article
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    Indirect Feedback Kalman Filter Based Sensor Fusion for Reducing Navigation Errors of an Autonomous Wheelchair by Soh, Ying Wei

    Published 2018
    “…Fusion of the wheel encoders and gyroscope was effected using indirect feedback Kalman filter algorithm. The algorithm was programmed in a small memory microcontroller to increase the portability of the wheelchair. …”
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    Final Year Project / Dissertation / Thesis
  18. 18

    Academic Achievement Prediction Model Using Neural Networks by Normaziah, Abdul Rahman

    Published 2002
    “…This model allows the system administrator to train and normalize data as well as trains. Once the model has been established by the administrator, the future student achievement can be forecast by the model. …”
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    Thesis
  19. 19

    Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows by Zhang, Shasha, Dong, Qiming, Yasin, Megat Al Imran, Fang, Ng Chwee

    Published 2026
    “…Preprocessing removes noise from text data, normalizes sentiment word lists and undertakes temporal transformation. …”
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    Article
  20. 20

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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    Article