Search Results - (( data generation using algorithm ) OR ( parameters estimation using algorithm ))
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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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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Generation gap used was 0.5 has shorten the algorithm convergence time without affecting the model accuracy.…”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…Generation gap used was 0.5 has shorten the algorithm conver-gence time without affecting the model accuracy.…”
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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). …”
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Accuracy of GeoWEPP in estimating sediment load and runoff from a tropical watershed.
Published 2011“…CLImate GENerator (CLIGEN) was used to estimate stochastic climatic parameters. …”
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Surface Moisture Content Retrieval from Visible/Thermal Infrared Images and Field Measurements
Published 2013“…In this study, NOAA/AVHRR satellite was used to estimate the surface temperature and satellite estimated soil moisture content as input parameters leading to estimate the evapotranspiration over Perak Tengah & Majung regions in Malaysia. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…As these methods are global optimizers, there is less possibility that they will fall in a local minima and are suitable for the selection of the parameters of the antecedent part. A comparative analysis of the optimal parameters with the randomly and manually generated parameters is presented here using noise-free and noisy Mackey-Glass time series data sets and a real world data set. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…The positive sequence measurement is use to estimate the positive sequence parameters which will generate inaccurate parameter estimates. …”
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Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review
Published 2015“…The three algorithms are evaluated for performance using three parameters; power efficiency, cost effectiveness, and amount of CO2 emissions. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…Besides, in comparison with the CTGAN data generated for the ML analysis, data generated from the finite element model used in the ML analysis has outperform the prediction than the CTGAN of synthetic and hybrid data. …”
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Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means
Published 2020“…Using a set of equations, these values then estimate the parameters of the triangular membership function. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Therefore, in this project, Principal Component Analysis (PCA) is used to reduce the number of parameters. The project is divided to several steps; in which the first step is to develop a conceptual model which can be used to generate both synthetic historical data and also simulated data. …”
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Final Year Project -
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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…The main scope of stage II is the prediction of future power generation by using generated weather data. Accordingly, the first aspect to point out is the generation of future climate parameters. …”
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Thesis
