Search Results - (( data visualization learning algorithm ) OR ( using optimization _ algorithm ))
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1
Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
2
Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…The study considers three fundamental parameters for measuring user comfort: thermal comfort, visual comfort, and indoor air quality (IAQ). Data from temperature, illumination, and CO2 sensors are collected to assess the indoor environment. …”
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Article -
3
Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Thesis -
4
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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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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Conference or Workshop Item -
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm
Published 2020“…We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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Article -
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Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024“…The findings show that that student's good performance in programming courses has a visual, active and sequential learning style.…”
Proceedings Paper -
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli
Published 2023“…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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Student Project -
9
Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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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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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. …”
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Monograph -
12
The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. …”
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Thesis -
13
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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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri
Published 2025“…This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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15
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 -
16
HELM based Reinforcement Learning for Goal Localization
Published 2016“…Hierarchical Extreme Learning Machine (H-ELM) algorithm was used to find good features for effective representation. …”
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Proceeding Paper -
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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Thesis -
18
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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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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Article -
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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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