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algorithms mc » algorithms _ (Expand Search), algorithms a (Expand Search), algorithm _ (Expand Search)
algorithm co » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm _ (Expand Search)
co function » cost function (Expand Search)
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
Published 2013Get full text
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Mobile robots obstacles avoidance using dynamic window approach
Published 2018Get full text
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Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network
Published 2020“…The CMP was the highest for the substrate with moisture content (%MC) in the range of 34% to 48%, and it decreased for %MC > 50%. …”
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Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
Published 2022“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”
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Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures
Published 2017“…The accurate model comparison on the standard CoNLL-2012 setting shows the benefit of more expressive loss functions.…”
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Blood Glucose Regulation Modelling and Intelligent Control
Published 2024Get full text
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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP
Published 2021Get full text
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
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Reinforcement Learning-Based School Energy Management System
Published 2020“…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”
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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition
Published 2019“…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …”
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Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Published 2021Get full text
doctoralThesis