Search Results - (( data visualization learning algorithm ) OR ( using optimization based algorithm ))
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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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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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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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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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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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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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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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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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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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Hierarchical extreme learning machine based reinforcement learning for goal localization
Published 2017“…The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. …”
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Proceeding Paper -
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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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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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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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14
Development of IoT-based automated dynamic emergency response system against fire incidents in academic building
Published 2023“…This study aims to address the need for improved firefighting systems in academic building by proposing the development of an IoT-based automated emergency response website. 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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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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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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Mean of correlation method for optimization of affective states detection in children
Published 2018“…At the moment, most of the studies on classification of affective states for children focus on visual observations and physiological cues, where all data collection for measuring physiological signals are contact-based and invasive. …”
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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. Finally, the optimal values are (P = 400 bar, T = 3.38 K 102, Y = 1.064 10ˉ³ mol fraction) using this model.…”
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Development of graphical interface software for solar flare monitoring system
Published 2023“…This new system is also at an optimal and sophisticated level compared to the technology that has been used. …”
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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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