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modeling algorithm » scheduling algorithm (Expand Search)
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modeling algorithm » scheduling algorithm (Expand Search)
spatial modeling » statistical modeling (Expand Search)
complement » implement (Expand Search), complementary (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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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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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025Subjects: “…Nature-inspired optimization algorithms…”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Design of adaptive arrays based on element position perturbations
Published 1993“…The authors report on the design of a digital feedback control system to provide null steering by controlling the array element positions automatically. The array comprises a signal processor, digital control algorithm (PID), stepper motors, shaft encoders, actuators and multiplexers. …”
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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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Adaptive bias simulated evolution algorithm for placement
Published 2001“…A new solution is evolved from current solution by relocating some of the solution elements. Elements with lower goodnesses have higher probabilities of getting selected for perturbation. …”
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An improved kernelization algorithm for r-Set Packing
Published 2010“…Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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An exact and general model order reduction technique for the finite element solution of elastohydrodynamic lubrication problems
Published 2017“…The technique is complemented with a splitting algorithm to alleviate the hurdle of solving an arising semidense matrix system. …”
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A kernelization algorithm for d-Hitting Set
Published 2010“…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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Fuzzy simulated evolution algorithm for topology design of campusnetworks
Published 2000“…The two main phases of the algorithm, namely, evaluation and allocation, have been fuzzified. …”
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get 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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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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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 FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS
Published 2020“…Comparison is also made with Esau–Williams (EW) algorithm, a well known constructive algorithm for the category of problems addressed in this work. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…This paper presents a parallel algorithm to solve the Clique Partitioning Problem, an NP-complete problem. …”
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