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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
Published 2024Get full text
doctoralThesis -
42
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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43
Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…This conclusion was achieved after preprocessing a number of data values from these data sets.</p><h2>Other Information</h2><p dir="ltr">Published in: Algorithms<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/a13080202" target="_blank">https://dx.doi.org/10.3390/a13080202</a></p>…”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
doctoralThesis -
46
Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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47
Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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masterThesis -
49
General applicability of genetic and simulated annealing algorithms for data mapping
Published 1995Get full text
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conferenceObject -
50
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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51
Convergence and steady-state analysis of the normalized least mean fourth algorithm
Published 2007“…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”
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Convergence and steady-state analysis of the normalized least mean fourth algorithm
Published 2007“…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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A comparison of data mapping algorithms for parallel iterative PDE solvers
Published 1995“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …”
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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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masterThesis -
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