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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”
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An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data. …”
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
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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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Multi-marker-LD based genetic algorithm for tag SNP selection
Published 2014“…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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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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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
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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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Brain Source Localization in the Presence of Leadfield Perturbations
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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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