Search Results - (( using optimization method algorithm ) OR ( data virtualization learning algorithm ))

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    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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    Conference or Workshop Item
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    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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    Monograph
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    Exploring clusters of rare events using unsupervised random forests by Z A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, N Hamzah

    Published 2022
    “…To identify the intrinsic structures in the minority class (the stroke group), Random Forest Clustering was used to produce the proximity matrix and fed to Partition around Medoid (PAM) clustering method to identify the optimal number of clusters. …”
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    Conference or Workshop Item
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    Multi-objective dynamic job shop scheduling optimization in manufacturing systems: A short review by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Hammad, Muhammad Yahya

    Published 2025
    “…This review brings together current research on the use of Multi-Objective Optimization (MOO) methods in dynamic scheduling, with particular attention to how energy cost optimization (ECO) is incorporated into real-time decision-making frameworks. …”
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    Article
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    Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

    Published 2025
    “…In today's technology-driven era, innovative methods for predicting behaviors and patterns are crucial. Virtual Learning Environments (VLEs) represent a rich domain for exploration due to their abundant data and potential for enhancing learning experiences. …”
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    Article
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    Performance comparison of non-invasive blood glucose level using artificial neural network and ultra-wide band antenna by Islam, Minarul Rafiqul, Sabira, Khatun, Kamarul Hawari, Ghazali, Mohd Mawardi, Saari, Shakib, Mohammed Nazmus, Mohamad Shaiful, Abdul Karim

    Published 2020
    “…Several experiments were carried out to investigate the optimal ANN learning algorithm (levenberg-marquardt (LM), resilient backpropagation (RP) and scaled conjugate gradient (SCG)) for performance comparison. …”
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    Conference or Workshop Item
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    A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning by Lim Jia Zheng, James Mountstephens, Jason Teo

    Published 2021
    “…This paper proposes a novel approach for 4-class emotion classification using eye-tracking data solely in virtual reality (VR) with machine learning algorithms. …”
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    Proceedings
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    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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    Undergraduates Project Papers
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    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

    Published 2018
    “…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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    Thesis