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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain
Published 2017“…In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012–31 March 2014 at three sites. …”
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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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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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Modeling and Control of a Robot Based Rehabilitation System for the Head-Neck Joint
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”
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A genetic algorithm for testable data path synthesis
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Data reductions and combinatorial bounds for improved approximation algorithms
Published 2016“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …”
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Distributed dimension reduction algorithms for widely dispersed data
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AI-based remaining useful life prediction and modelling of seawater desalination membranes
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