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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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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
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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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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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Development of Energy-efficient Algorithms for Wireless Sensor Networks
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Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems
Published 2022“…Therefore, the paper discusses the development of the Lévy flight-based reptile search algorithm with local search capability and evaluates its potential against challenging power systems engineering optimization problems. …”
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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…In this paper, the most important literature and previous studies related to the subject of the study were presented, where nearly 30 researches were referred to develop a theoretical framework related to SSA and other improved algorithms and to compare SSA with other systems. …”
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Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery
Published 2018Get full text
doctoralThesis -
9
Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…Two ML models were developed in this study. Model 1 predicts the variations of the flame radius with time, equivalence ratio, and turbulence intensity, whereas model 2 predicts the variations of the turbulence flame speed with the operating parameters. …”
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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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Arithmetic optimization algorithm: a review and analysis
Published 2024“…A metaheuristic algorithm called arithmetic optimization algorithm (AOA) is developed to solve various optimization problems. …”
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Topics in graph algorithms
Published 2003“…Coping with computational intractability has inspired the development of a variety of algorithmic techniques. …”
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Application of Red Deer Algorithm in Optimizing Complex functions
Published 2021“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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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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Kernelization algorithms for the vertex cover problem
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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…The proposed algorithm out performed fairly well the results that exists from previous studies. …”
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Empirical comparison of regression test selection algorithms
Published 2001“…In the maintenance phase, the regression test selection problem refers to selecting test cases from the initial suite of test cases used in the development phase. In this paper, we empirically compare five representative regression test selection algorithms, which include: Simulated Annealing, Reduction, Slicing, Dataflow, and Firewall algorithms. …”
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