Search Results - (( problem implementation _ algorithm ) OR ( parameter estimation method algorithm ))
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1
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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Article -
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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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3
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 -
4
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…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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5
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. …”
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Final Year Project -
6
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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7
Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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Fraud detection in telecommunication industry using Gaussian mixed model
Published 2013“…The expectation maximization algorithm is used to estimate the parameter of the model such that the initial values of the algorithm is determined using the kernel method. …”
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Conference or Workshop Item -
10
SKF-based image template matching for distance measurement by using stereo vision
Published 2018“…The traditional algorithm to solve image matching problem take a lot of memory and computational time. …”
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Book Chapter -
11
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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12
Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
Published 2018“…Integrating a trajectory correction algorithm in the navigation control can overcome this problem. …”
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13
Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…On the one side, the estimation Transfer Function (TF) of these motors is considered a significant problem in most previous studies which causes bad controller design, if the low estimation accuracy. …”
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15
Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission
Published 2011“…It is designed based on the Shaped VBR (SVBR) algorithm and was implemented in the Network Simulator 2 (ns-2). …”
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Analysis of robot localisation performance based on extended kalman filter
Published 2015“…First is the performance of the algorithm using different parameters in which different velocities and number of landmarks have been used to determine the accuracy of the localisation method. …”
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The largest studentized residual test for bad data identification in state estimation of a power system
Published 2015“…The reporting results are presented showing that the method is most powerful and effective for practical implementation in conventional procedures of the state estimation problem. …”
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Article -
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Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner
Published 2022“…As a recommendation, further researchers can implement other methods in solving nonlinear least square problems, such as the Levenberg-Marquadt method and Broyden's. …”
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Student Project -
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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Thesis -
20
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Thesis