Search Results - (( parameters estimation process algorithm ) OR ( simulation optimization method algorithm ))
Search alternatives:
- parameters estimation »
- estimation process »
- process algorithm »
- method algorithm »
-
1
Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…In last decade, there has been increasing interest in simulating the natural evolutionary process in solving hard optimization problems. …”
Get full text
Get full text
Research Reports -
2
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. …”
Get full text
Get full text
Get full text
Article -
3
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
Get full text
Get full text
Thesis -
4
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
Get full text
Get full text
Thesis -
5
Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”
Article -
6
Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…Two novel hierarchical structures are presented which extend the applicability of previous model based double iterative loop techniques to non-convex problems. The methods incorporate integrated system optimisation and parameter estimation which utilizes process measurements to achieve real process optimality inspite of model reality differences. …”
Get full text
Get full text
Article -
7
A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana
Published 2020“…Three performance measurements are used in this paper to evaluate the proposed PSOHS: the standard deviation, nonlinear least squared error, and computational time. The proposed algorithm outperformed the other two methods, namely Simulated Annealing and the downhill simplex method, and proved that PSOHS is a more suitable algorithm for estimating kinetic parameter values.…”
Get full text
Get full text
Get full text
Article -
8
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. …”
Get full text
Get full text
Monograph -
9
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. …”
Get full text
Get full text
Get full text
Article -
10
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
Get full text
Get full text
Final Year Project -
11
An improved Multipath Estimating Delay-Lock-Loop method based on Teager-Kaiser operator
Published 2018“…Simulation results show that the algorithm can accurately estimate the number of multipath signal components, and improve the estimation accuracy of the signal parameters. …”
Get full text
Get full text
Get full text
Article -
12
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
Get full text
Get full text
Article -
13
Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
Get full text
Get full text
Conference or Workshop Item -
14
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
Get full text
Get full text
Article -
15
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
Get full text
Get full text
Article -
16
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. …”
Get full text
Get full text
Thesis -
17
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). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
18
Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…The performances of both estimation and control algorithms are illustrated by simulation results. …”
Get full text
Get full text
Conference or Workshop Item -
19
A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
Get full text
Get full text
Article -
20
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
Get full text
Get full text
Thesis
