Search Results - (( developing function learning algorithm ) OR ( its implementation model algorithm ))

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  1. 1

    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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    Article
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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
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    Age And Gender Recognition Mobile App by Wee, Quo Lung

    Published 2023
    “…Therefore, this study aimed to develop age and gender recognition mobile application using deep learning algorithm. …”
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    Final Year Project Report / IMRAD
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    SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

    Published 2005
    “…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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    Final Year Project
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    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
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    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions 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
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    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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    Thesis
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    Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability by Rusdi, Nur ‘Afifah, Zamri, Nur Ezlin, Kasihmuddin, Mohd Shareduwan Mohd, Romli, Nurul Atiqah, Manoharam, Gaeithry, Abdeen, Suad, Mansor, Mohd. Asyraf

    Published 2024
    “…Based on the findings, the development of the new systematic SAT and the implementation of the Hybrid Black Hole algorithm to optimize the retrieval capabilities of DHNN to achieve multi-objective functions result in updated final neuron states with high diversity, high attainment of global minima solutions, and produces states with a low similarity index. …”
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    Article
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    Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

    Published 2023
    “…This algorithm is capable of surmounting the aforementioned drawbacks especially premature convergence, through its reward-based dynamic leader assignment and self-learning strategies. …”
    text::Thesis
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    Digital assistant for workspace apps by See, Ling Xuan

    Published 2022
    “…The proposed system will be achieved by applying machine learning to train the digital assistant model for it can study and execute every Teams’ function or the function combinations and allow user customization on its steps to complete certain task. …”
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    Final Year Project / Dissertation / Thesis
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    Auxiliary-based extension of multi-tasking sequence-to-sequence model for chatbot answers by Palasundram, Kulothunkan

    Published 2021
    “…Since its inception for the machine-learning-based translation problem domain in 2014, the sequence-to-sequence (Seq2Seq) training approach has shown remarkable progress in developing chatbots. …”
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    Thesis
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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
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    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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    Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

    Published 2018
    “…This means that any changes on the cover media (c) could lead to the identification of the stego media (s), which contains the secret message (m). Thus, developing a steganographic algorithm to use cover media (c) without raising attention is the most challenging task in data hiding. …”
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    Thesis
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    Implementation of repetitive control algorithm in reducing vibration using MATLAB/SIMULINK / Mohamad Zuhairy Mohamed by Mohamed, Mohamad Zuhairy

    Published 2008
    “…In this report, it analyzes an application of repetitive control algorithm that deal with periodic disturbance.. To investigates the possibility of using a truncated finite impulse response (FIR) model approximation to implement a well-known gradient type repetitive control algorithm. …”
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    Student Project
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