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  1. 1

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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    Thesis
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    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

    Published 2024
    “…The recent development of knowledge in fractional calculus introduced an advanced superior operator known as fractal–fractional derivative (FFD). …”
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    Article
  3. 3

    Automatic marking system for programming subject by Chan, Jin Yee

    Published 2023
    “…This application handle execution of anonymous code that could be malicious securely by running the code in an isolate environment. …”
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    Final Year Project / Dissertation / Thesis
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    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

    Published 2025
    “…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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    A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato... by Alsa’Di, Kawthar, Nik Long, Nik Mohd Asri

    Published 2025
    “…Moreover, a new hybrid technique which is the combination of deep learning artificial neural network and finite difference method (FDL-ANN) is developed to approximate the solution of higher order VFIDEs. …”
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    Article
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    Development of a hybrid dynamic fuzzy encoder and decoder model for colour QR code by Badawi, Bakri

    Published 2022
    “…A new colour QR code algorithm known as a Fuzzy QR code (FQR code) was proposed to solve the problems faced by current colour QR codes. …”
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    Thesis
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    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…We enhanced the Q-Learning algorithm for action selection based on potential action abilities and proposed a tool, namely CrashDroid, that allows the automation of testing context-aware Android applications. …”
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    WAVELET-DCT BASED IMAGE CODER FOR VIDEO CODING APPLICATIONS by Chai, Beng Seow

    Published 2007
    “…This project is about the implementation ofWavelet-DCT intra-frame coder for video coding applications. Wavelet-DCT is a novel algorithm that uses Forward Discrete Wavelet Transform (DWT) to compute DCT. …”
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    Final Year Project
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    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…It has been applied in many practical applications. For most of the cases of the shortest route finding, the Dijkstra's algorithm is known to be an optimal search algorithm. …”
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    Thesis
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    Predictive modelling of nanofluids thermophysical properties using machine learning by Olanrewaju, Alade Ibrahim

    Published 2021
    “…This thesis aimed to develop machine learning algorithms to estimate the thermophysical properties of commonly used nanofluids. …”
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    Thesis
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    WA VELET-DCT BASED IMAGE CODER FOR VIDEO CODING APPLICATIONS by GANI, REGINA

    Published 2008
    “…The algorithm allows truncation of intermediate coefficient through DWT. …”
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    Final Year Project
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    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…We propose a tool, namely the Crash Droid, that allows the automation of testing context-aware Android applications. We utilise the Q-Learning algorithm to compare actions, including context-based actions, to effectively detect crashes and achieve a higher code coverage.…”
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    Article
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