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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
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
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
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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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach
Published 2024journal::journal article -
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Exploring clusters of rare events using unsupervised random forests
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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Virtual Models for Real-World Learning: The Development and Evaluation of a Patient Simulator for Eye Disability Diagnosis
Published 2024thesis::master thesis -
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Multi-objective dynamic job shop scheduling optimization in manufacturing systems: A short review
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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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The reliability of VR supports various variations in learning, including learning programming algorithms. …”
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction
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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Performance comparison of non-invasive blood glucose level using artificial neural network and ultra-wide band antenna
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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A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning
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
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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Machine learning algorithms on price and rent predictions in real estate: A systematic literature review / Muhamad Harussani Abdul Salam ... [et al.]
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Performance comparison of feature selection methods for prediction in medical data
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Proceeding Paper -
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
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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