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method algorithm » mould algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
finding » findings (Expand Search)
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Natural optimization algorithms for optimal regression testing
Published 1997“…The optimal regression testing problem is that of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. …”
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conferenceObject -
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Simulated Annealing and Genetic Algorithms for Optimal Regression Testing
Published 1999“…The experimental results, which include a comparison with previous algorithms, show that the simulated annealing and genetic algorithms find the optimal or near-optimal number of retests within a reasonable time. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Aiming to tackle these obstacles, we have derived a new computational method in order to identify conserved regions of Single Nucleotide Polymorphisms (SNPs) on autosomal chromosomes that are differentiable in different populations. Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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masterThesis -
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
Published 2024Get full text
doctoralThesis -
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Test case generation for path coverage. (c2000)
Published 2000Get full text
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masterThesis -
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A genetic algorithm for corrective retesting. (c1995)
Published 1995Get full text
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
Published 2013Get full text
doctoralThesis -
14
Tensile Test Optimization Using the Design of Experiment and Soft Computing
Published 2023“…The objective of this study is to investigate the effects of temperature, the area of the contact point, and the operator on the tensile test of brass samples. This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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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. …”