Search Results - (( data optimization model algorithm ) OR ( data visualization learning algorithm ))
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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2
IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management
Published 2025“…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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Proceeding -
3
Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…This research contributes novel insights into the application of clustering algorithms in banking, proposing pragmatic solutions for efficient data analysis and campaign optimization. …”
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4
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…Criminal risk is predicted using classification models for a particular time interval and place. 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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Conference or Workshop Item -
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Hierarchical extreme learning machine based reinforcement learning for goal localization
Published 2017“…This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. …”
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Proceeding Paper -
6
The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…It is observed that the ResNet101v2 model pairing up with an optimized SVM pipeline is able to achieve the best classification accuracy of 95% for training, validation and testing data.…”
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Thesis -
7
Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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8
Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. Gathering and evaluating a large amount of data is time and effortintensive. …”
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Monograph -
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
Published 2023“…Despite extensive research employing machine learning algorithms like convolutional neural networks (CNN), challenges remain concerning input data processing, emotion classification scope, data size, optimal CNN configurations, and performance evaluation. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…These methods present a robust system that enables fully automated identification and removal of artifacts from EEG signals, without the need of visual inspection or arbitrary thresholding. The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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Thesis -
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Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz
Published 2025“…The CRISP-DM methodology was followed to apply machine learning algorithms, namely Random Forest, Decision Tree, and Naive Bayes, to the data gathered in the library which is traffic, book rentals, and questionnaires. …”
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12
Development of IoT-based automated dynamic emergency response system against fire incidents in academic building
Published 2023“…The proposed system leverages IoT technology, wireless and bluetooth sensor networks to gather real-time data from various sensors and devices installed in the site and uses machine learning algorithms to predict and prevent potential fire incidents. …”
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Predicting the onset of acute coronary syndrome events and in-hospital mortality using machine learning approaches / Song Cheen
Published 2023“…This study used a comprehensive methodology to investigate the relationship between air pollution and ACS patient outcomes utilizing machine learning (ML) algorithms, including: 1) Linear Regression, 2) Logistic Regression, 3) Support Vector Machine (SVM), 4) Random Forest (RF), 5) XGBoost, 6) Naïve Bayes (NB), and 7) Stacked Ensemble ML utilizing data from the National Cardiovascular Disease Database (NCVD) Malaysia registry and air quality data from the Department of Environment (DOE) Malaysia. …”
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Thesis -
14
Machine Learning Workflow to Predict Remaining Useful Life (RUL) of Equipment
Published 2019“…One of the most popular machine learning approaches is employed in the prediction workflow which is the Artificial Neural Network (ANN) algorithm, due to its capability to learn from a large volume of data points and high prediction accuracy. …”
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Final Year Project -
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization
Published 2022“…ADA-LR was selected as the primary model according to numerical and visual analysis. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process
Published 2008“…This would simplify the task of obtaining fuzzy rules from machining data. Beside that, the model is compared with other artificial intelligence approaches, such as fuzzy logic, neural network and genetic algorithm. …”
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Thesis -
19
Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2021“…This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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Proceeding Paper