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Improvement and application of particle swarm optimization algorithm
Published 2025“…The proposed GAPSO algorithm will achieve an average relative error reduction of 2%, accuracy will improve by 96%, the maximum performance will be achieved by 95%, the F1 score will develop by 95%, and the training error cure rate will improve by 94%.…”
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The use of the Bayesian approach in the formation of the student's competence in the ICT direction
Published 2019“…The paper gives a small introduction about the competence of students and explores the possibility of using Bayesian networks in the formation of the competence of an IT trainer. Developed an integrated algorithm for the formation of the competence of training in the direction of IT.…”
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Conference or Workshop Item -
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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Final Year Project -
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Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin
Published 2024“…This research also aims to discuss several issues and problems that is associated to deep networks such as overfitting, scaling issues and training time. This study is conducted through development of a Modular Deep Neural Network (MDNN) and several experiments to enhance its training capabilities. …”
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Thesis -
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Multi-Agent Reinforcement Learning For Swarm Robots Formation
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Monograph -
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Prediction of PVT properties in crude oil systems using support vector machines
Published 2023Subjects:Conference paper -
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Analysis of detection system for cover tape offset in the tap and reel process using neural net time series method
Published 2025“…Notably, the Bayesian Regularization (BR) training algorithm outperformed the Scaled Conjugate Gradient (SCG) training algorithm for cover tape offset's predictive analysis, exhibiting lower Mean Squared Error (MSE) with 0.0015874 for BR compared to 0.0017839 for SCG, consistently lower Mean Absolute Error (MAE) values, stronger linear correlations, and superior overall performance. …”
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Handwritten character recognition system for online learning using Recurrent Neural Network (RNN) / Nur Nabilah Shafiqah Rosli
Published 2022“…The purpose of this research to develop handwritten character recognition system by using Recurrent Neural Network (RNN) algorithm. …”
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Student Project -
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Development of Malay word pronunciation application using vowel recognition
Published 2016“…In Malaysia, many researchers focus on developing speaker independent systems for training or articulation therapy or to assist language learners to learn about Malay Language or Bahasa Malaysia.Accuracy, noise robustness and processing time are concerns when developing speech therapy systems.In this study, a Malay word pronunciation test application was developed using the first 3 format and fundamental frequencies in an effort to improve pronunciation in Malay.This application was developed using Matlab and uses a vowel recognition algorithm classified using MLP classification technique.The application was developed and tested on UUM undergraduate students.For vowel classification, when fundamental frequency was added, 3-format feature vowel classification rate increased by 1.55% for male gender and 1.48% for female. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Thesis -
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Academic Exercise -
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The prediction of diesel engine NOx emissions using artificial neural network / Mohd. Mahadzir Mohammud and Khairil Faizi Mustafa
Published 2003“…In order to reduce or to control diesel engine polluting emissions, the formation mechanism of NOx can be predicted. A neural network model is developed to obtain the NOx emission concentration under various operating condition. …”
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The prediction of diesel engine NOx emissions using artificial neural network / Mohd Mahadzir Mohammud and Khairil Faizi Mustafa
Published 2003“…In order to reduce or to control diesel engine polluting emissions, the formation mechanism of NOx can be predicted. A neural network model is developed to obtain the NOx emission concentration under various operating condition. …”
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System setup on jetson nano for smart crowd covid monitoring system
Published 2022“…Labels can be downloaded in one of the many formats that are supported.…”
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Undergraduates Project Papers -
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Deep reinforcement learning-based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles
Published 2022“…Moreover, to demonstrate the accuracy of the safety efficiency analysis, multiple training runs of the neural networks in respect of training performance, speed of training, success rate, and stability of rewards with a trade-off between exploitation and exploration during training are presented. …”
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Deep reinforcement learning based driving strategy for avoidance of chain collisions and its safety efficiency analysis in autonomous vehicles
Published 2022“…Moreover, to demonstrate the accuracy of the safety efficiency analysis, multiple training runs of the neural networks in respect of training performance, speed of training, success rate, and stability of rewards with a trade-off between exploitation and exploration during training are presented. …”
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Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada
Published 2021“…The results of feedforward neural network (FFNN) with back-propagation algorithm and the BR regularization technique for 9 input parameters produced satisfactory performances in TOC prediction (R2 = 94 and 89) in training and validation phases, respectively, and for the Tmax prediction (R2 = 88 and 86) with 5 input parameters in the training and validation phases, respectively. …”
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A new mobile malware classification for call log exploitation
Published 2024journal::journal article -
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Design, development and evaluation of a game-based learning application for room housekeeping
Published 2024“…The transition of practical skills training into a digital format presents distinct challenges and opportunities within the hospitality industry. …”
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