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processing algorithm » processing algorithms (Expand Search)
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Editorial on the Special Section on Algorithms, Circuits, and Systems for Signal Processing at the Edge
Published 2021“…<p dir="ltr">Technological trends alongside with the unprecedented growth of the data generated by devices sparsely distributed, most of them mobile devices, cannot be supported by traditional approaches and processing systems. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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Detecting Game Bugs Using Genetic Algorithms And Reachability Analysis Of Colored Petri Nets Models
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50
Towards Scalable Process Mining Pipelines
Published 2023“…Contributions have covered the spectrum of better algorithms, richer comparison metrics, and movement towards online analysis for process data. …”
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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Prediction of EV Charging Behavior Using Machine Learning
Published 2021“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…The huge amounts of data generated by media sensors in health monitoring systems, by medical diagnosis that produce media (audio, video, image, and text) content, and from health service providers are too complex and voluminous to be processed and analyzed by traditional methods. …”
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Mining airline data for CRM strategies. (c2006)
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A New Parallel Genetic Algorithm Model
Published 2020“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”
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A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
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Machine Learning Model for a Sustainable Drilling Process
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doctoralThesis