Search Results - (( simulation estimation method algorithm ) OR ( rate optimization method algorithm ))
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025“…The new DFGPSO algorithm is specifically designed to address the intrinsic challenges in PV modelling, such as local optima entrapment and slow convergence rates that typically hinder traditional optimization methods. …”
Article -
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Monograph -
3
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…While the automatic method focus on optimization which is normally computer based. …”
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Final Year Project -
4
Satellite attitude determination utilizing measurement sensor data and kalman filtering
Published 2006“…This assessment was done by using Monte Carlo methods to simulate these sensors. Using only star measurements an optimal satellite orientation estimate is found using the method of least squares, and the particular algorithm invoked is referred to ESOQ2 method. …”
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Article -
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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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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 -
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Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency
Published 2016“…The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation, design of experiments (DOE) and particle swarm optimization (PSO) algorithm. …”
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Article -
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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 -
10
On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems
Published 2020“…The optimization of the antenna selection and optimal transmission power with impact of pilot reuse sequences were achieved, by applying Newton’s method and the Lagrange multiplier. …”
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Thesis -
11
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The simulated results and analysis demonstrate an excellent agreement between the proposed algorithm and non-Newtonian fluids flow attributes. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The simulation results of GA, PSO and AIS showed that the GA1 algorithm which used the first main temperature objective function gives the best temperature value (35. 7 0C) compared with other algorithms, followed by PSO1 (70.2 0C), then AIS1 (112.8 0C). …”
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Thesis -
14
Product optimization of a fed-batch fermentation process
Published 2007“…From this two optimization approaches, it is possible to estimate the optimal operating conditions as substrate feed rate so that the systems presents high performance within threshold value limit. …”
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Conference or Workshop Item -
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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Thesis -
16
Comparison And Assessment Of Methods Used To Estimate Egfr In Ckd Patients: The Role Of Clinical Pharmacist And Direct Medical Costs
Published 2021“…This study aimed to evaluate GFR estimating algorithms for medication dosing in CKD patients. …”
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Thesis -
17
Large-scale kinetic parameters estimation of metabolic model of escherichia coli
Published 2019“…Seven highly sensitive kinetic parameters in the model response were considered in the optimization problem. Estimation of the 7th kinetic parameters by the PSO method provides a good performance of the model in terms of accuracy.…”
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Article -
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Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)
Published 2022“…Meanwhile, high perturbation signal will cause the fluctuation that led to unstable power production. Thus, new method was introduced which is Particle Swarm Optimization (PSO) that is expected to improve the performance of conventional MPPT. …”
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Proceedings -
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. …”
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Thesis -
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Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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