Search Results - (( time estimation methods algorithm ) OR ( pre estimation method algorithm ))
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Power System State Estimation In Large-Scale Networks
Published 2010“…The Weighted Least Squares (WLS) method is the most popular technique of SE. This thesis provides solutions to enhance the WLS algorithm in order to increase the performance of SE. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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3
Implementation of Autoregressive(AR)Method to Pre-Filter the Set of Measurements
Published 2009“…This paper describes a pre-screening process to identify the bad measurements and the measurement weights before WLS estimation method employed in SE is performed. …”
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4
Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…Besides, the proposed method obtains satisfactory outcomes in EV drive cycles, estimating MAE of 0.193% and 0.346% in DST and FUDS cycles, respectively, at 25�C. � 2016 IEEE.…”
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Implementation of Autoregressive (AR)Method to Pre-Filter the Set of Measurements
Published 2009“…This paper describes a pre-screening process to identify the bad measurements and the measurement weights before WLS estimation method employed in SE is performed. …”
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6
An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…In the second method, a new traffic estimation method is proposed using Fuzzy C-Mean (FCM) clustering and Minimum Description Length (MDL). …”
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7
A Subspace Approach with Pre-whitening for Measurements of Latencies in Visual Evoked Potentials
Published 2011“…Alternatively, a VEP estimation scheme based on a single VEP trial can be developed to reduce VEP recording time and minimize fatigue on subjects. …”
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A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise
Published 2010“…The simulation results produced by the post-modified SSA2 algorithm, show a higher degree of consistencies in detecting the VEP's P100, P200, and P300 peaks, in comparisons to the pre-modified SSA1 method. …”
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9
Generalized Subspace Approach for Measurements of Visual Evoked Potentials
Published 2009“…The results of comprehensively simulated data involving SNR from 0 to -11 dB indicate that the GSA schemes outperform the other three methods. The GSA estimators produce the lowest failure rate and average errors, and their performance is relatively independent of the given SNR in contrary to the other methods. …”
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10
Generalized Subspace Approach for Measurement of Latencies in Visual Evoked Potentials
Published 2010“…The results of comprehensively simulated data involving SNR from 0 to -11 dB indicate that the GSA schemes outperform the other three methods. The GSA estimators produce the lowest failure rate and average errors, and their performance is relatively independent of the given SNR in contrary to the other methods. …”
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11
Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. …”
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Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
Published 2013“…Similar attack strategies have been estimated by using one of the two proposed methods. …”
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13
Fingerprint classification : a BI-resolution approach to singular point extraction
Published 2004“…This thesis presents a singular point extraction method using two layers of information, without pre-processing of the image. …”
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Improved static and dynamic FBG sensor system for real-time monitoring of composite structures
Published 2017“…The voltage normalization algorithm has reduced the output voltage variations from 26 data/minute to 17 data/minute with the elimination of pre-calibration each time before use. …”
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15
An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles
Published 2022“…Among different algorithms, this study focuses on modelling the non- recursive phasor estimation method in a power Simulink environment for a standard test system equipped with a developed algorithm to detect the fault zone. …”
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A development of a damage monitoring system using an embedded fiber Bragg grating sensors
Published 2019“…The voltage normalization algorithm has reduced the output voltage variations from 26 data/minute to 17 data/minute with the elimination of pre-calibration each time before use. …”
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18
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…Fortunately, these issues can be addressed with machine learning methods such as deep learning(DL) due to its capacity in modeling highly non-linear phenomena, powerful generalization capability, and fast run-time. …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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20
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…Wearable devices, smart-phones and ambient environments devices are equipped with variety of sensors such as accelerometers, gyroscopes, magnetometer, heart rate, pressure and wearable camera for activity detection and monitoring. These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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