Search Results - (( emotional detection sensor algorithm ) OR ( based optimization mead algorithm ))*
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Human emotion classifications for automotive driver using skin conductance response signal
Published 2016“…Risky driving is an attitude associated with human states of emotion. Emotions detected using facial and body movements, sounds and physiological changes which required multiple and bulky instruments such as camera, voice recorder and sensors. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…Emotion recognition is found to be an important aspect of the interaction between human being where emotion influences human in daily life. …”
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Face emotion recognition using artificial intelligence techniques
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A review of chewing detection for automated dietary monitoring
Published 2022“…Articles that reported chewing activity characteristics and various wearable sensors used to detect chewing activities automatically were reviewed. …”
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