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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 kernelization algorithm for d-Hitting Set
Published 2010“…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …”
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24
Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Published 2023“…This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed Hybrid Finite Element (MHFE) approximations. An original MHFE-based formulation of the two-phase flow model is taken as a reference for the development of the BCPR preconditioner, in which the set of system unknowns comprises both element and face pressures, in addition to the cell saturations, resulting in a $$3\times 3$$ 3 × 3 block-structured Jacobian matrix with a $$2\times 2$$ 2 × 2 inner pressure problem. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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26
A new approach to record clustering for large databases. (c1997)
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27
Algorithmic Study of Online Multi-Facility Location Problems
Published 2022“…In this paper, we study MFL in the online setting, in which client requests are not known in advance but are revealed to the algorithm over time. …”
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Natural optimization algorithms for the cross-dock door assignment problem
Published 2016“…The results indicate that the SS algorithm outperformed the GA, particularly for large-sized problems with a diverse reference set.…”
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A method for test scheduling using an evolutionary approach. (c2000)
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Parallel scatter search algorithms for exam timetabling. (c2009)
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31
Using genetic algorithms to optimize software quality estimation models
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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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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995)
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35
DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
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36
A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017“…We present experimental results that demonstrate the effectiveness of our method while outperforming reported techniques.…”
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Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates
Published 2024“…The whole piezoelectric multilayered plate’s dynamic stiffness is then built, from which its circular frequencies are computed with the help of the Wittrick-Williams algorithm. A detailed discussion is provided on the implementation aspects, followed by some numerical examples to assess the robustness, accuracy and effectiveness of the proposed method. …”
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Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
Published 2021“…The study explores sentiment analysis using different machine learning algorithms on dialectal Arabic text dataset. In this study, we used twitter as our data source. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Additionally, it was able to identify several differentiable regions in the real data set and on different chromosomes. However, we noticed that chromosomes 1, 3 and 6 had the highest occurrence rate of differentiable motifs (9, 8 and 6 motifs respectively). …”
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masterThesis