Search Results - (( probable detection method algorithm ) OR ( parameter estimation using algorithm ))
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1
Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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Thesis -
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. …”
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4
Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…The existence of outliers in circular-circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using minimum spanning tree method. …”
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5
GENETIC FUZZY FILTER BASED ON MAD AND ROAD TO REMOVE MIXED IMPULSE NOISE
Published 2010“…In this thesis, a genetic fuzzy image filtering based on rank-ordered absolute differences (ROAD) and median of the absolute deviations from the median (MAD) is proposed. The proposed method consists of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization using genetic algorithms (GA) to perform efficient and effective noise removal. …”
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Thesis -
6
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Thesis -
7
Microcrack Detection And Noise Reduction In Integrated Circuit Packages
Published 2018“…Three algorithms are tested and evaluated in terms of microcrack detection and noise reduction which are probability based thresholding, histogram equalization, and modified Perona-Malik’s anisotropic diffusion methods. …”
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Monograph -
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Estimation in spot welding parameters using genetic algorithm
Published 2007“…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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10
Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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Thesis -
11
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
Published 2024“…The proposed ESMA was used to resolve the problem of estimating PV parameters based on the empirical current-voltage (I-V) data. …”
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An analysis of low complexity of 5G-MIMO communication system based CR using hybrid filter detection
Published 2022“…Thus, a 5G-MIMO based CR communication system has been developed to enhance the spectrum by employing a spectrum sensing (SS) algorithm. This recommended SS algorithm, based on the hybrid filter detection (HFD) method, employs the Cosine law for filtering the traffic signal, and then enables segmentation by applying the Welch algorithm. …”
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15
Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The output is measured from the model and used to adapt the adjustable parameters. During the iterative procedure, the differences between the real plant and the model used are captured by the adjustable parameters. …”
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17
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses
