Search Results - (( variable learning based algorithm ) OR ( using electro methods algorithm ))
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1
Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm
Published 2007“…Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. …”
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2
Self-tuning control of an electro-hydraulic actuator system
Published 2011“…Due to time-varying effects in electro-hydraulic actuator (EHA) system parameters, a self-tuning control algorithm using pole placement and recursive identification is presented. …”
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3
Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…An active method which has received much attention is the use of Active Noise Control (ANC) system which involves an electro acoustic system that cancels unwanted noise using the principle of superposition. …”
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4
The Effects Of Weightage Values With Two Objective Functions In iPSO For Electro-Hydraulic Actuator System
Published 2021“…The PID controller parameters will be tuned by using the iPSO algorithm to get the lowest overshoot percentage and steady-state error. …”
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5
Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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6
Classical and metaheuristic optimizations performance in an electro-hydraulic control system
Published 2022“…A classical and metaheuristic optimization methods, which are gradient descent (GD) and particle swarm optimization (PSO) algorithm are used to obtaining the optimal gains of both controllers. …”
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7
Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…The current dialogue act recognition models, namely cue-based models, are based on machine learning techniques, particularly statistical ones. …”
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8
Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…Based on the identical dataset, the GA-BP and PSO-BP algorithms are also compared to the PCA-BAS-ENN algorithm. …”
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9
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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10
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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11
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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12
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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13
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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14
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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15
Modeling and Position Control of Fiber Braided Bending Actuator Using Embedded System
Published 2023“…Data from the system input and output are used by the black box method. Thus, the voltage supplied to the electro-pneumatic regulators and the position (angle) of the FBBA system are used to collect input–output data in this study. …”
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16
One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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17
Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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18
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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19
Normalized SPSA for Hammerstein model identification of twin rotor and electro-mechanical positioning systems
Published 2025“…The effectiveness of the proposed method was validated by modeling the actual systems, which included the twin-rotor system (TRS) and the electro-mechanical positioning system (EMPS). …”
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20
Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
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