Search Results - (( using estimation means algorithm ) OR ( using optimization method algorithm ))
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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Thesis -
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System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…It was superior to the clustering algorithm methods in most real-world datasets with means ARI of over 0.35. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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Conference or Workshop Item -
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Conference or Workshop Item -
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…Overall, the proposed methods achieve a 4.26% mean absolute error of chewing count estimation.…”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…Real-coded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…Overall, the proposed methods achieve a 4.26% mean absolute error of chewing count estimation.…”
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Hybrid firefly algorithm–neural network for battery remaining useful life estimation
Published 2024“…Accurately estimating the remaining useful life (RUL) of batteries is crucial for optimizing maintenance, preventing failures, and enhancing reliability, thereby saving costs and resources. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm
Published 2012“…Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed…”
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Proceeding Paper -
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Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…This means that the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved. …”
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