Search Results - (( java application swarm algorithm ) OR ( pattern extraction path algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Feature extraction: hand shape, hand position and hand trajectory path
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Animal voice recognition for identification (ID) detection system
Published 2011“…While the voice pattern classification will be done by using DTW algorithm. …”
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Dog voice identification (ID) for detection system
Published 2012“…While the voice pattern classification will be done by using DTW algorithm. …”
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NN with DTW-FF Coefficients and Pitch Feature for Speaker Recognition
Published 2006“…This paper proposes a new method to extract speech features in a warping path using dynamic programming (DP). …”
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Local DTW coefficients and pitch feature for back-propagation NN digits recognition
Published 2006“…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition
Published 2006“…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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Advances in materials informatics: A review
Published 2024“…Conventional ML models are simple and interpretable, relying on statistical techniques and algorithms to learn patterns and make predictions with limited data. …”
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A hybrid environment control system combining EMG and SSVEP signal based on brain-computer interface technology
Published 2021“…The feature in terms of the common spatial pattern (CSP) has been extracted from four classes of SSVEP response, and extracted feature has been classified using K-nearest neighbors (k-NN) based classification algorithm. …”
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