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Boosting the visibility of services in microservice architecture
Published 2023“…Our research also analyzed the boosting algorithms, namely Gradient Boost, XGBoost, LightGBM, and CatBoost to improve the overall performance. …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…The reported accuracy dramatically outperforms the previous algorithms, including gradient tree boosting (GTB), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and linear discriminant analysis (LDA). …”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk
Published 2025“…Additionally, an online classifier is developed for streaming data, combining online PCA with a kernel-based recursive classifier using a stochastic approximation algorithm. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”
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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy
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doctoralThesis -
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Data mining approach to predict student's selection of program majors
Published 2019“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
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The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…Recent advances in algorithm design have shown a growing interest in seeking exact solutions to many hard problems. …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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doctoralThesis -
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Efficient methods and techniques for the open-shop scheduling problem. (c2006)
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masterThesis -
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The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques
Published 2018“…In this study I’ve split one dataset of patients who have attended to emergency departments in Abu Dhabi hospitals to two datasets (Respiratory and Cardiac), then applied the data mining algorithms on each dataset and one time on the original dataset. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…My research aims to develop a data-driven decision support framework for fleet management, focusing on leveraging advanced algorithms, including decision trees and random forests, to generate domain-specific AI models. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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A parallel search tree algorithm for vertex cover on graphical processing units. (c2013)
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masterThesis -
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