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modeling algorithm » scheduling algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
making algorithm » cosine algorithm (Expand Search)
data modeling » data models (Expand Search), spatial modeling (Expand Search)
data making » data mining (Expand Search)
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61
Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
62
Correlation Clustering with Overlaps
Published 2020“…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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masterThesis -
63
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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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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
Published 2023“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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66
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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67
Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures
Published 2025“…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …”
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68
Brain Source Localization in the Presence of Leadfield Perturbations
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doctoralThesis -
69
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 -
70
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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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 -
76
Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…However, with the huge increase in data size, sophisticated models have to be created which require big data platforms. …”
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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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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. …”