Search Results - (( square evaluation method algorithm ) OR ( simulation optimization method algorithm ))
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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Structural optimization of 4-DOF agricultural robot arm
Published 2024“…The best algorithm, i.e., the PSO algorithm, is evaluated by calculating mean square error (MSE of 0.00108527), root mean square error (RMSE of 0.01678), mean absolute error (MAE of 0.004286081), and end-effector position error (error of 0.080557045), where the best algorithm has the lowest value of error.…”
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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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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A Hybrid of Particle Swarm Optimization and Harmony Search to Estimate Kinetic Parameters in Arabidopsis thaliana
Published 2020“…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.…”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…Next, the weighted and transformed features were used to train Linear Discriminant Function (LDA) and to evaluate the constructed rule. The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Active vibration control of a flexible beam structure using chaotic fractal search algorithm
Published 2017“…The objective of this work was to evaluate the performance of chaos-enhanced Stochastic Fractal Search (CFS) optimization algorithm in modeling and vibration control of flexible beam system. …”
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination
Published 2022“…This may be extremely helpful both practically and theoretically in the PV system simulation, optimization, and evaluation. Numerous stochastic methods have been widely utilized in recent decades to tackle the parameter extraction optimization problem. …”
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Optimization of coded signals based on wavelet neural network
Published 2015“…We performed a simulation to evaluate the effectiveness of the proposed method. …”
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Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…The calculated parameter of the overlapped samples for hour-tracking varies from 74.12% for GMRT, to 58.46 % for 25th generation configuration, and 53.36% 150th generation configurations. Finally, the algorithm is able to reduce SLL to -25.23 dB. The third method develops a new algorithm named Division Algorithm (DA) to solve the optimization problems. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…Secondly, the K-value-calculating algorithm computes the optimal number of clusters. …”
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin
Published 2025“…Essential phases of the project include data collection, data preprocessing, and the implementation of the Particle Swarm Optimization-Random Forest price prediction algorithm. …”
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Particle Swarm Optimization Algorithm Based Fuzzy Controller for Solid-State Transfer Switch Toward Fast Power Transfer and Power Quality Mitigation
Published 2024“…The optimized fuzzy controller shows superior performance in terms of transfer time, detection time, and harmonic reduction in comparison to those obtained without the PSO algorithm in all tested cases. � 1972-2012 IEEE.…”
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Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…Several statistical measures such as Root Mean Squared Error (RMSE), Coefficient of Determination (R2), Ratio of Performance to Deviation (RPD), and Standard Error (SE) are used to evaluate the superiority of the proposed methods. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…Besides, it has achieved up to 60% and 65% respectively for a fixed number of 128 and 512 BS antennas compared to ZF algorithm. The results of the increase in the number of BS antennas with a fixed number of users, the proposed method achieved up to 20% and 60% compared to regular BD and ZF algorithms respectively. …”
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Integration Of Travel Time Zone For Optimal Siting Of Emergency Facilities
Published 2008“…Fire stations in Jakarta Selatan were chosen for simulation. Two algorithms, Greedy Adding (Add) and Greedy Adding with Travel Time Evaluation (GAT), were applied to solve the optimization problem of the MSAP. …”
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