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developing based » developing a (Expand Search), developing 21st (Expand Search)
data algorithms » jaya algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
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Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
Published 2006“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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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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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…The classification performance is determined via different metrics for various GA-based ANN classifiers using data extracted from the healthy and faulty data of the GCPV system. …”
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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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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…We demonstrated the applicability of feature engineering techniques such as data imputation, transformation (e.g., scaling, centering, etc.), and data balancing using several case studies and the proposed semi-automated framework. …”
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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. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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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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Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms
Published 2018“…Various weighting functions and intelligent search algorithms have been developed for that purpose and will be presented here. …”
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Mining airline data for CRM strategies. (c2006)
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Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems
Published 2022“…Therefore, the paper discusses the development of the Lévy flight-based reptile search algorithm with local search capability and evaluates its potential against challenging power systems engineering optimization problems. …”
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Developing a UAE-Based Disputes Prediction Model using Machine Learning
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Social spider optimization algorithm: survey and new applications
Published 2024“…This algorithm has been developed over time, resulting in many versions besides theories and findings. …”
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A genetic algorithm for testable data path synthesis
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A neural networks algorithm for data path synthesis
Published 2003“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level 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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