An Iterative Error Correction Procedure for Single Sheet Testers Using FEM 3D Model by Robert Krobot, Martin Dadić

“…This paper proposes a correction procedure for the measurement of anhysteretic BH curve and power losses, based on the finite element model (FEM) and SST apparatus. …”
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Iterative Shaping of Error Patterns For Normal Syndrome Decoding of Iterative Codes by X. H. Ren, V. K. Kanapelka, V. Yu. Tsviatkou

“…As a result, the known methods for generating the error pattern library become non sufficient. This paper proposed a mathematical model, a generator structure, and an algorithm for fast generation of an error pattern library based on the iterative expansion of the error patterns, which makes it possible to reduce the number of generated redundant error patterns by orders of magnitude and significantly shorten the computational complexity in comparison with the known approaches.…”
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Automated image acquisition system for visual inspection with positioning error correction by Toma TANIGUCHI, Hidenori NAKATSUJI, Isamu NISHIDA

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Automatic Correction of Labeling Errors Applied to Tomato Detection by Ángel Eduardo Zamora Suárez, Gerardo Antonio Alvarez Hernandez, Juan Irving Vasquez, Hind Taud, Abril Valeria Uriarte-Arcia, Erik Zamora

“…Accurate labeling is critical for training reliable deep learning models in agricultural applications. However, manual labeling is often error-prone, especially when performed by non-experts, and such errors (modeled as noise) can significantly degrade model performance. …”
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Design of aperture radar auxiliary technology based on array mathematical model and statistical characteristic calculation by Ji Yang, Ying Fan, Shuqing Yang

“…Two error correction algorithms, active correction and iterative self-correction, are proposed by designing error correction algorithms based on the matrix space spectrum correction error concept. …”
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A Broyden Correction Image Reconstruction Algorithm for Electrical Capacitance Tomography System by CHEN Yu, XIA Zong-ji, LI Hong-bo, ZHOU Yu-jia

“…After the analysis of the basic principles of the ECT system, to solve the problem of electrical capacitance tomography system, we deduced a mathematical model of Broyden Correction algorithm and analyzed the convergence of the algorithm using the monotony of the iterative error. …”
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Array amplitude-phase and mutual coupling error joint correction method based on sparse Bayesian by Ding WANG, Weigang GAO, Zhidong WU

“…In the actual array direction finding system, there are often a variety of errors such as amplitude and phase, mutual coupling, which lead to serious deterioration of array direction finding performance.In order to solve the problem of array direction finding misalignment in the presence of low signal-to-noise ratio, small snapshots and multiple errors, the spatial sparsity of signals were introduced, and Bayesian sparse reconstruction technology was used to solve the passive correction and joint estimation of array signal azimuth in the presence of amplitude-phase and mutual coupling errors.The over-complete model of the received signal with error was constructed, and the posterior probability density function of the received signal was obtained.The EM algorithm was used to iteratively optimize the probability density function to solve the corresponding parameters.At the same time, the CRLB of array error and signal azimuth was derived, and by experimental simulation verifies the effectiveness of the proposed method.…”
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Array amplitude-phase and mutual coupling error joint correction method based on sparse Bayesian by Ding WANG, Weigang GAO, Zhidong WU

“…In the actual array direction finding system, there are often a variety of errors such as amplitude and phase, mutual coupling, which lead to serious deterioration of array direction finding performance.In order to solve the problem of array direction finding misalignment in the presence of low signal-to-noise ratio, small snapshots and multiple errors, the spatial sparsity of signals were introduced, and Bayesian sparse reconstruction technology was used to solve the passive correction and joint estimation of array signal azimuth in the presence of amplitude-phase and mutual coupling errors.The over-complete model of the received signal with error was constructed, and the posterior probability density function of the received signal was obtained.The EM algorithm was used to iteratively optimize the probability density function to solve the corresponding parameters.At the same time, the CRLB of array error and signal azimuth was derived, and by experimental simulation verifies the effectiveness of the proposed method.…”
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Enhanced Wind Power Forecasting Using Graph Convolutional Networks with Ramp Characterization and Error Correction by Xin He, Yichen Ma, Jiancang Xie, Gang Zhang, Tuo Xie

“…This is integrated with a bidirectional long short-term memory network to enhance prediction performance during power fluctuation periods. Finally, a dynamic error feedback correction mechanism is introduced to iteratively refine the prediction results in real time. …”
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Improved Coulomb collision operator for kinetic ion transport with EMC3-EIRENE simulating Nitrogen seeding in medium density ITER L-mode scenario by D. Harting, D. Reiser, S. Rode, J. Romazanov, P. Börner, Y. Feng, H. Frerichs, A. Knieps

“…Previous simulations with the kinetic ion transport module of EMC3-EIRENE for Nitrogen seeding in a medium density ITER L-mode scenario showed that the currently simplified Coulomb collision model of EIRENE leads to a strongly overestimated confinement of the kinetic ions in the magnetic mirror regions. …”
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Thermo-hydraulic performance of concentric tube heat exchangers with turbulent flow: Predictive correlations and iterative methods for pumping power and heat transfer by Samer Ali, Chadi Nohra, Jalal Faraj, Talib Dbouk, Mahmoud Khaled

“…These correlations showed an average error of less than 2.33% when compared with the CFD data. …”
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Direction-of-Arrival Estimation Based on Variational Bayesian Inference Under Model Errors by Can Wang, Kun Guo, Jiarong Zhang, Xiaoying Fu, Hai Liu

“…To address this limitation, this paper proposes an orientation estimation method based on variational Bayesian inference to combat non-uniform noise and gain/phase error. The gain and phase errors of the array are modeled separately for calibration purposes, with the objective of improving the accuracy of the fit during the iterative process. …”
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Snowmelt runoff model (SRM) for regulated watersheds with regulation-correction by Ninad Bhagwat, Xiaobing Zhou, Raja Nagisetty, Liping Jiang, Glenn Shaw, Martha Apple, Jeremy Clotfelter

“…In all scenarios, comparison between observed and regulation-corrected streamflow showed improved performance across multiple model assessment metrics. …”
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Research on BER performance of the OAM-SK FSO communication system with wavefront phase correction by Shuang LI, Ping WANG, Tao LIU, Yuting PAN, Wei WANG

“…On the basis of Gerchberg-Saxton (GS) algorithm and angular-spectrum theory, an improved wavefront phase correction algorithm to the Laguerre-Gaussian (LG) beams was proposed for the orbital angular momentum-shift keying (OAM-SK) modulation-based free space optical (FSO) communication system under weak atmospheric turbulence.The light field distributions of the probe beam at transmitter and receiver were regarded as the input of the improved wavefront phase correction algorithm.And the correction phase mask was iteratively calculated to correct the distorted LG beams, thereby alleviating the inter-model crosstalk caused by atmospheric turbulence.Simulation results show that the improved wavefront phase correction algorithm is superior to the conditional GS algorithm.And with the increase of the refractive-index structure parameter, the bit error rate (BER) performance of the OAM-SK FSO communication system is significantly improved.…”
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Research on BER performance of the OAM-SK FSO communication system with wavefront phase correction by Shuang LI, Ping WANG, Tao LIU, Yuting PAN, Wei WANG

“…On the basis of Gerchberg-Saxton (GS) algorithm and angular-spectrum theory, an improved wavefront phase correction algorithm to the Laguerre-Gaussian (LG) beams was proposed for the orbital angular momentum-shift keying (OAM-SK) modulation-based free space optical (FSO) communication system under weak atmospheric turbulence.The light field distributions of the probe beam at transmitter and receiver were regarded as the input of the improved wavefront phase correction algorithm.And the correction phase mask was iteratively calculated to correct the distorted LG beams, thereby alleviating the inter-model crosstalk caused by atmospheric turbulence.Simulation results show that the improved wavefront phase correction algorithm is superior to the conditional GS algorithm.And with the increase of the refractive-index structure parameter, the bit error rate (BER) performance of the OAM-SK FSO communication system is significantly improved.…”
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An iterative approach for deriving and solving an accurate regression equation by Manaye Getu Tsige, Andreas Malcherek, Ivo Baselt

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An accurate voltage measurement method for electric field inversion in power lines with dual-stage model error reduction by Haitao Yang, Zhensheng Wu, Shuai Zheng, Zhongli Zhang, Yongjie Nie

“…First, in the first stage, an optimization simulated charge model (CSM) is established, which can minimize the electric field inversion error via an optimization model. …”
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Model Modification of the Mill Transmission System Based on the PSO-BP Neural Network by Tao Zheng, Bao Xianle, Guo Qintao, Zhou Tianyang

“…This method approximates the nonlinear mapping relationship between the two by improving the back propagation (BP) neural network, combines with the actual structural response, and uses the generalization property of the neural network to obtain the numerical value of the model design parameters. After the correction, the frequency error is reduced from a maximum of 18% to about 4%, and the error range of the correction coefficient is all within 0.5%, while obviously improving the accuracy of the finite element model. …”
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How many dollars are in the sea? Estimating sand dollar (Echinarachnius parma) abundance using an iteratively trained convolutional neural network and generalized additive models by Sara Vanaki, Deborah R. Hart, Jui-Han Chang

“…We employ Generalized Additive Models (GAMs) that use the confidence levels combined with covariates to estimate the probabilities that a detection is correct as well as the number of targets in an image. …”
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Real-world defocus deblurring via score-based diffusion models by Yuhao Li, Haoran Fang, Xiang Lei, Qi Wang, Gang Hu, Jiaqing Dong, Zilong Li, Jiabin Lin, Qiegen Liu, Xianlin Song

“…To address this problem, we propose a high-resolution iterative deblurring method for real scenes driven by a score-based diffusion model. …”
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