Search Results - (( data optimization method algorithm ) OR ( parameter estimation focus algorithm ))
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1
Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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Article -
2
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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Thesis -
3
A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023“…This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). …”
Conference paper -
4
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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5
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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Final Year Project -
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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7
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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8
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…However, no research is focused on the parameter estimation method to remedy the problem of multicollinearity which is due to multiple HLPs. …”
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9
Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization
Published 2025“…The dataset used in this study is a battery RUL dataset retrieved from an open-source platform Kaggle, which consists of more than 15,000 rows of time series data. The study introduces a hybrid model that integrates TCN with Artificial Fish Swarm Algorithm (AFSA), a bio-inspired optimization technique designed to fine-tune TCN parameters. …”
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Article -
10
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…The new procedure called Bayesian Random Forest (BRF) focuses on modification of terminal node parameter estimation and selection of random subsets for splitting. …”
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11
Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. …”
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12
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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13
Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…Machine learning is also a focus in this work, which was employed to process and classify FRF data in terms of damage. …”
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14
Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
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Conference or Workshop Item -
15
Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
Published 2013“…The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. …”
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16
Analysis of multicomponent transient signals using music superresolution technique
Published 2008“…The parameters of focus in this paper are the number of components and decay constants. …”
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Proceeding Paper -
17
VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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18
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Article -
19
Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain
Published 2014“…Initially, the research focuses on three main tasks. First, voltage profile on source distribution system is estimated. …”
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20
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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