Search Results - (( parameter estimation from algorithm ) OR ( parameter optimization sensor algorithm ))
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1
A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…During optimization, within 100 iterations, the chewing count is reduced by 12.9% from its first iteration. …”
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2
Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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3
Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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4
A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…During optimization, within 100 iterations, the chewing count is reduced by 12.9% from its first iteration. …”
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5
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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8
Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi
Published 2013“…Simulation is done by using the observer which uses optimal feedback gain as an example of process from algorithm design to verification of logic. …”
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9
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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10
Classification of heart sound signals for the detection of heart diseases / N. Shamsuddin and M. N. Taib
Published 2012“…The obtained frequency pattern features were fed to the FFNN and trained using Resilient Backpropagation (RPROP) algorithm. With optimized learning parameter of 0.07, the network gave its best performance at 32-220-6. …”
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Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
Published 2023“…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. …”
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Accurate localization method combining optimized hybrid neural networks for geomagnetic localization with multi-feature dead reckoning
Published 2025“…The eight-dimensional BiLSTM (8DBiLSTM) algorithm is subsequently proposed for heading estimation in dead reckoning, which effectively improves the heading accuracy. …”
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13
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The optimization technique involved from two points to four points and end with six points. …”
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14
Hilbert transform of FFT pruned cross correlation function for optimization in time delay estimation
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15
Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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16
A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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17
Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper
Published 2017“…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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Parameter adaptation for ant colony system in wireless sensor network
Published 2019“…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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Embedded Dual Band Rfid Based Blood Glucose Monitoring System For Internet Of Medical Things
Published 2020“…In the reliability analysis using ANOVA and DOE statistical methods, the result validates that the number of hop and number of end node significantly affects the PDR performance of conventional CSMA/CA. These two parameters are then taken into account in experimental setup for performance evaluation of the enhanced CSMA/CA (EN-CSMA/CA) algorithm that uses an external interrupt mechanism and a cross layer approach. …”
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20
On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee
Published 2021“…In continuation of the first framework, the proposed MTF measurement algorithms are evaluated experimentally as a blur kernel estimation method for spatially varying and invariant blur removal. …”
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