Search Results - (( data transformation method algorithm ) OR ( parameter optimization method algorithm ))
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1
Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform
Published 2014“…Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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Final Year Project -
2
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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Conference or Workshop Item -
3
Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Article -
4
Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…The hybrid method, IDBA-AFW, aims to enhance the original IDBA by incorporating the Adaptive Floyd-Warshall algorithm for graph transformation and optimization. …”
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Thesis -
5
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
6
Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
7
Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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Thesis -
8
Bio-lubricant production based on optimum epoxidized oleic acid using in situ peracid mechanism / Tunku Arif Zafri Tunku Ozir
Published 2022“…The identity of the bio-lubricants were confirmed using Fourier Transform Infrared (FTIR) Analysis. Other than that, a kinetic modelling was performed using MATLAB, genetic algorithm optimization tool as a few reserch can be found to support the method. …”
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Student Project -
9
Evolutionary tuning of modular fuzzy controller for two-wheeled wheelchair
Published 2012“…Due to its signficant advantages over other searching methods, a genetic algorithm approach is used to optimize the scaling factors of the MFC and results show that the optimized parameters give better system performance for such a complex, highly nonlinear two-wheeled wheelchair system.…”
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Article -
10
Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform
Published 2014“…Thus, this project is carried to do assisted history matching and to determine whether Recursive least square as optimization method and Discrete cosine transform as parameter reduction method can be combined or not. …”
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Final Year Project -
11
Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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Conference or Workshop Item -
12
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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Thesis -
13
Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel
Published 2016“…Results show that the defect detection algorithm able to detect defect only on the scratch area and able to read the Ga value at detected scratch line and transform it to surface roughness measurement at considerably good level of accuracy compared with manual method. …”
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Thesis -
14
New optimization technique to design the core of three-phase transformer
Published 2019“…In this study, an intelligent algorithm employing particle swarm optimization (PSO) has been used to get the optimum T-joint design of a core in a three-phase transformer. …”
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15
Optimal model order selection for Transient Error Autoregressive Moving Average (TERA) MRI reconstruction method
Published 2008“…These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). …”
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Proceeding Paper -
16
Optimal model order selection for transient error autoregressive moving average (TERA) MRI reconstruction method
Published 2008“…These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). …”
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Article -
17
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…So,this optimization method can help to save time and cost of the process. …”
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Thesis -
18
Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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Thesis -
19
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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Thesis -
20
