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preprocessing algorithm » processing algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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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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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.…”
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Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations
Published 1992“…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. These are simulated annealing, genetic algorithms and neural networks. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Published 2023“…Therefore, we designed a dedicated two-stage strategy, inspired by the CPR algorithm, where a block preconditioner is used for the pressure part with the aim at exploiting the inner $$2\times 2$$ 2 × 2 structure. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…This paper aims to identify the impact of each design parameter on the shear behavior of BFRC-BFRP one-way slabs using a fractional factorial design of experiment (DOE). A 3D finite element model was first developed and validated against available experimental results. …”
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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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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…It is worth noting that the injection moulding process does not incorporate a type-2 fuzzy neural network (T2FNN). However, in this particular investigation, T2FNN was employed to replicate the mechanical stress model associated with dashboard injection moulding. …”
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Design of adaptive arrays based on element position perturbations
Published 1993Get full text
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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”
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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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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
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Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. …”
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Adaptive bias simulated evolution algorithm for placement
Published 2001Get full text
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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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