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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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64
Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
Published 2024Get full text
doctoralThesis -
65
Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
66
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
doctoralThesis -
67
Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…In this work, we propose a new model to enhance auto-indexing Arabic texts. Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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masterThesis -
68
Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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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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An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
Published 2019“…Finally, the experimental results prove the improvements provided by our hash based algorithm over previously suggested models.…”
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masterThesis -
74
Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT
Published 2021“…Specifically, Novel Supportive Twin Delayed DDPG trains the user model to authenticate specific regions. As it is considered one of the most open and scalable interacting platforms of information, it successfully helps in the positive transfer of different kinds of data between devices in more significant and local operations of the industry. …”
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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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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”
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79
Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
80
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. …”