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  1. 1
    Feedforward neural network for solving particular fractional differential equations

    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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  2. 2
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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  3. 3
    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
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  4. 4
    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer

    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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  5. 5
    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control

    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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  6. 6
    A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operator

    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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  7. 7
    Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions

    Polynomial neural network for solving Caputo-conformable fractional Volterra–Fredholm integro-differential equation with three-point non-local boundary conditions by Alsa’di, Kawthar, Nik Long, Nik Mohd Asri, Senu, Norazak, Eshkuvatov, Z.K.

    Published 2025
    “…A hybrid technique, combining a polynomial neural network (PNN) with an extreme learning machine algorithm without using any activation functions, is developed. …”
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  8. 8
    Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil

    Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil by Idris, Siti Aishah, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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  9. 9
    Predictive modelling of nanofluids thermophysical properties using machine learning

    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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  10. 10
    Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations

    Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

    Published 2024
    “…In the second part of the thesis, we developed the Hilfer fractal-fractional derivative definition. …”
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  11. 11
    An improved vulnerability exploitation prediction model with novel cost function and custom trained word vector embedding

    An improved vulnerability exploitation prediction model with novel cost function and custom trained word vector embedding by Hoque M.S., Jamil N., Amin N., Lam K.-Y.

    Published 2023
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  12. 12
    Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning

    Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

    Published 2023
    “…The resultant semantic maps are inserted into the decoder fraction to obtain the full-resolution probability maps. …”
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  13. 13
    Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine

    Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine by Jahirul, M.I., Saidur, Rahman, Masjuki, Haji Hassan

    Published 2009
    “…The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. …”
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  14. 14
    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique

    Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

    Published 2017
    “…Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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  15. 15
    Parametric investigation of battery thermal management system with phase change material, metal foam, and fins; utilizing CFD and ANN models

    Parametric investigation of battery thermal management system with phase change material, metal foam, and fins; utilizing CFD and ANN models by Najafi Khaboshan, Hasan, Jaliliantabar, Farzad, Abdul Adam, Abdullah, Panchal, Satyam, Azarinia, Amiratabak

    Published 2024
    “…Finally, an artificial neural network model is developed using the backpropagation learning technique coupled with the gradient descent optimization algorithm. …”
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  16. 16
    Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz

    Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz by Abd Aziz, Nur Hasyimah

    Published 2020
    “…Next, the system was successfully developed by implementing the best CNN model as a classifier. …”
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  17. 17
    Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization

    Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization by Nader Ibrahim Namazi, Sameer Alshehri, Rawan Bafail, Bader Huwaimel, Amal M. Alsubaiyel, Ali H. Alamri, Ahmed D. Alatawi, Hossam Kotb, Mohd Sani Sarjadi, Md. Lutfor Rahman, Mohammed A.S. Abourehab

    Published 2022
    “…Finally, the optimal values are (P = 400 bar, T = 3.38 K 102, Y = 1.064 10ˉ³ mol fraction) using this model.…”
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