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research algorithm » search algorithm (Expand Search)
boosting algorithm » cosine algorithm (Expand Search)
method algorithm » mould algorithm (Expand Search)
data research » do research (Expand Search)
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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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Boosting the visibility of services in microservice architecture
Published 2023“…These assessments can be performed by means of a live health-check service, or, alternatively, by making a prediction of the current state of affairs with the application of machine learning-based approaches. In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …”
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The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…Exact algorithms often follow the classical search-tree based recursive backtracking strategy. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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Modulation With Metaheuristic Approach for Cascaded-MPUC49 Asymmetrical Inverter With Boosted Output
Published 2020“…<p>This work introduces a 49-level Asymmetrical Inverter (AMLI) with boosted output based on the cascaded operation of two 7-Level Modified Packed U-Cell inverters (MPUC-7). …”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…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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A genetic algorithm for testable data path synthesis
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Distributed dimension reduction algorithms for widely dispersed data
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General applicability of genetic and simulated annealing algorithms for data mapping
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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