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41
Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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42
Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
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Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms
Published 2022“…In the first method, the CVaR measurement was modeled by means of DEA, then Particle Swarm Optimization (PSO) and the Imperial Competitive Algorithm (ICA) were used to solve the proposed model. …”
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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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45
Intelligent Rapidly-Exploring Random Tree Star Algorithm
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46
Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Consequently, scholars have begun to focus on document classification problem, offering various methods to address this issue. Researchers have utilized diverse data sources, such as citations, metadata, content, and hybrids, in their approaches.In these sources, the meta-data-based approach stands out for research paper classification due to its availability at no cost. …”
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48
Three-phase simulated annealing algorithms for exam scheduling
Published 2003“…We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. Our experimental results show that 3PSA produces good exam schedules, which are better than those of the clustering heuristic procedure.…”
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Distributed dimension reduction algorithms for widely dispersed data
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51
A genetic algorithm for testable data path synthesis
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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54
Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…”
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55
Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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60
Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis