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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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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…The accuracy of these algorithms was assessed with standard statistical measures and ground truth data randomly collected in Prince Edward Island, Canada. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022Subjects: “…Data clustering…”
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022Subjects: “…orthogonal learning (OL)…”
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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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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019Subjects: Get full text
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024Subjects: -
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization
Published 2025“…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …”
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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