Search Results - (( simulation optimization modified algorithm ) OR ( using estimation using algorithm ))
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1
A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator
Published 2021“…The modified algorithm is called Discrete Simulated Kalman Filter Optimizer (DSKFO). …”
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2
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
Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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4
LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…Empirical studies using these univariate and multivariate models show that the BCD algorithms estimate less irrelevant thresholds compared to the approximation group LASSO algorithms of group least angle regression (GLAR). …”
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UMK Etheses -
5
Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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6
Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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Article -
7
Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Simulation results show that high resolution estimates of decay constants can be obtained when the above signal processing techniques are used to analyse multi exponential signals with varied signal-to-nose ratio (SNR) . …”
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8
Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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Thesis -
9
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, it really demands skill and experience on the part of simulation engineer. Today, tremendous efforts are made to develop Automatic History Matching algorithms. …”
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Final Year Project -
10
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. …”
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11
An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization
Published 2019“…By considering the ASVs as swarm robotics testing platforms, each algorithm is evaluated and benchmarked against several existing algorithms through simulation studies. …”
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Thesis -
12
A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise
Published 2010“…SNR values can be as low as -10 dB in real clinical environments. The simulation results produced by the post-modified SSA2 algorithm, show a higher degree of consistencies in detecting the VEP's P100, P200, and P300 peaks, in comparisons to the pre-modified SSA1 method. …”
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13
Shunt active power filter with modified synchronous reference frame technique and fuzzy logic current controller for harmonic mitigation
Published 2017“…The simulation and experimental results show ability of the proposed algorithms to accurately estimate harmonic reference signal which was utilized in switching pulses for the SAPF. …”
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Thesis -
14
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. …”
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15
Hybrid particle swarm optimization for robust digital image watermarking
Published 2011“…This paper presents an image watermarking algorithm for the optimization between robustness and transparency which is recently considered as one of the most challenging issues. …”
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16
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Thesis -
17
A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator
Published 2021“…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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18
Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…The third step employs the support vector machine algorithm to calculate prediction values. To demonstrate the effectiveness of the developed procedure, we used both simulation and real-life data examples. …”
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19
Optimized clustering with modified K-means algorithm
Published 2021“…Testing on real data sets showed consistency results as the simulated ones. Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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Thesis -
20
Design of self-tuning minimum effort active noise control with feedback inclusion architecture
Published 2009“…It was found that the optimal controller designed using this technique which is constrained only by the accuracy of the two models identified using recursive least squares algorithm, yields good cancellation level. …”
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