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modeling algorithm » scheduling algorithm (Expand Search)
spatial modeling » statistical modeling (Expand Search)
element based » event based (Expand Search)
rf algorithm » rd algorithm (Expand Search), _ algorithms (Expand Search)
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Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams
Published 2021“…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …”
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CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments
Published 2024“…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …”
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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“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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Design of adaptive arrays based on element position perturbations
Published 1993Get full text
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”
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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization
Published 2025“…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …”
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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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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
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An exact and general model order reduction technique for the finite element solution of elastohydrodynamic lubrication problems
Published 2017“…This work presents an exact and general model order reduction (MOR) technique for a fast finite element resolution of elastohydrodynamic lubrication (EHL) problems. …”
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A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates
Published 2024“…The obtained results are verified by comparison with published ones based on conventional approaches.…”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
Published 2024Get full text
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
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Fuzzy simulated evolution algorithm for topology design of campusnetworks
Published 2000“…We present an approach based on the simulated evolution algorithm for the design of campus network topology. …”
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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. …”
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MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
Published 2022“…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…A parallel simulator, based on PVM, was implemented for the proposed algorithm on a Linux Cluster. …”
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