Linear Pseudo-Measurements Filtering for Tracking a Moving Underwater Target by Observations with Random Delays by Alexey Bosov

“…The observation model is characterized by limited prior knowledge of the measurement errors distribution, specified only by its first two moments. …”
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Computer vision-based detection of liquid levels within cylindrical tanks in wastewater treatment by MA Huanhuan, LI Yunbei, ZHANG Yuanxin, HE Yu, SHI Ningning, FAN Anrui, ZHOU Linhao, HUANG Biaobing, HONG Shuangxi, ZHANG Xiaoju

“…Incorporating a deviation compensation can reduce the error to 0.01 mL, demonstrating the robustness and potential of the system for engineering application.…”
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A virtual-component-embedded equivalent circuit model for lithium-ion battery state estimation by Zelin Guo, Yiyan Li, Zhenghao Zhou, Chen Zhang, Zheng Yan, Mo-Yuen Chow

“…Last, the battery online state of charge (SOC) estimation is achieved based on the proposed hybrid model to demonstrate its application value. Simulation results on two real-world battery datasets show that the proposed hybrid model can achieve 18%–75% SOC estimation error reduction under varying operating conditions and on average 62% error reduction across different aging cycles, compared with the First-Order ECM.…”
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轨迹再现机构的模糊稳健优化设计方法 by 郭惠昕, 张世安, 何哲民, 桂乃磐

“…The method is able to control the movement error in design principle and the stochastic movement error caused by the manufacture error, and also can make the movement precision of mechanism match up to the tolerance of each dimension in reason. …”
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Advances and Emerging Trends in UAV Sensor Data Fusion Technology by Xiong Liukun, Zheng Ningning

“…The proposed precision-cost-power consumption triangle constraint criterion guides the combination of multispectrum and RTK-GNSS to balance 95% classification accuracy with 10 cm localization error in agricultural monitoring. Typical application verification shows that the bionic radar-vision system achieves 0.32 m positioning accuracy in the occlusion environment (41% improvement compared with the traditional method), and the LiDAR-photogrammetry combined leveling technology improves the absolute accuracy of terrain modeling by 23%. …”
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Dual-parameter identification based on model reference adaptive system for five-phase induction motor by Xinguo HOU, Xiangyu LUO, Xuan TU

“…When encountering abrupt changes in stator resistance under transient load conditions, the identification error remains below 5%, showing errors of 8.7% at half-load and 13.7% at full-load.…”
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Analisis Kontrol Aplikasi Untuk Menghasilkan Keakuratan Dalam Kelengkapan Informasi Pada Siklus Pendapatan Adorable Projects by Bobbyansyah Bobbyansyah, Elsje Kosasih

“…Purpose - Application control is control in the company's business processes to prevent, detect, and correct transaction errors and irregularities. …”
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Integral equation for numerical solution of stationary quantum-mechanical problems by Sergey Yu. Knyazev

“…The numerical solution error increases with the number of the energy eigenvalue. …”
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Observability Degree-Based AUV Single Beacon Navigation Trajectory Optimization with Range-Only Measurements by Huapeng Yu, Xu Zhou

“…To find out the optimum path to utilize range-only measurements, a novel observability degree-based analysis method is proposed, which gives a quantitative insight into convergence characteristics of the error states by using the eigenvalues of the normalized error covariance matrix. …”
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Prediction of the remaining useful life of a milling machine using machine learning by Abbas Al-Refaie, Majd Al-atrash, Natalija Lepkova

“…Several ML algorithms were applied and the results were evaluated using five measures involving Accuracy, Mean Absolute Error (MAE), Mean Squared Error (MSE), R-squared, and R-squared adjusted. …”
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Methodology for Deriving Parameters for Optimization Models of Systems of Flexible Energy Resources by Lukas Peter Wagner, Alexander Fay

“…The use of a predefined and validated optimization model avoids modeling errors, but parameterization is still necessary and error-prone. …”
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Precise motion control for a space mining robot based on improved African vultures optimization by Baiyi Wang, Xinhua Liu, Marek Rydel, Dezheng Hua, Rafal Stanislawski, Hui Wang, Ke Feng, Zhixiong Li

“…Space mining robots can develop and utilize abundant mineral resources in the outer space to solve the problem of the depletion of earth mineral resources. However, the motion errors of space mining robots in complex environments on the outer space surface of asteroids greatly hinder its applications. …”
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Boosting Safety Protocol Compliance with Eye-Tracking in Chemical Plants by Yangyi Xia, Yulin Zhao, Wu Song

“…The compliance assessment is based on five key metrics: reaction time, operational accuracy, attention focus, error count, and corrective response time. Results showed that eye-tracking-enhanced training reduced reaction time by 25%, improved accuracy by 15%, increased attention focus by 20%, and decreased errors by 30%. …”
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The Weight Distributions of a Class of Cyclic Codes with Three Nonzeros over 𝔽3 by Xiaogang Liu, Yuan Luo

“…Cyclic codes have efficient encoding and decoding algorithms. The decoding error probability and the undetected error probability are usually bounded by or given from the weight distributions of the codes. …”
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A hierarchical simulation framework incorporating full-link physical response for short-range infrared detection by Mingze Gao, Lixin Xu, Shiyuan Hu, Xiaolong Shi, Jiaming Gao, Yanjiang Wu, Huimin Chen

“…The evaluation results of the root mean square error (RMSE) and the Pearson correlation coefficient (PCC) show that the simulated data and the measured data achieve good consistency, and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals. …”
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Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models by Zainab Al-Ibraheemi, Samaher Al-Janabi

“…This research addresses both programming and application challenges. Programming challenges include high computational demands and the trial-and-error nature of parameter determination in deep learning, mitigated by using GWO. …”
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Improving the inversion accuracy of shallow shear wave velocity structure based on microtremor method: A case study of Haikou Jiangdong New District by ZHANG Qian, WU Xiaojie, ZHONG Zhoucan, CAI Shuiku

“…A large error change is mainly caused by an interface with a small velocity difference, and the inversion is more sensitive to an interface with a small velocity difference.   …”
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Comprehensive Stiffness Modeling and Evaluation of an Orthopedic Surgical Robot for Enhanced Cutting Operation Performance by Heqiang Tian, Mengke Zhang, Jiezhong Tan, Zhuo Chen, Guangqing Chen

“…Experimental validation confirms model fidelity, with prediction errors generally below 5%. Cutting experiments on porcine femurs demonstrate real-world applicability, achieving average stiffness prediction errors below 3%, and under 1% in key directions. …”
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Novel Recurrent neural networks for efficient heat transfer analysis in radiative moving porous triangular fin with heat generation by Sana Ullah Saqib, Umar Farooq, Nahid Fatima, Yin-Tzer Shih, Ahmed Mir, Lioua Kolsi

“…The effectiveness of Recurrent Neural Networks (RNNs) is rigorously proved through extensive experiments, demonstrating iterative convergence curves for mean squared error, control metrics of optimization and error distribution via histograms.The mean absolute percent error (MAPE), mean absolute error (MAE), and Nash-Sutcliffe efficiency (NSE) are all nearly zero, while the coefficient of determination (R2) is close to 1.Furthermore, there is strong evidence of the prediction accuracy and dependability of the RNN in the regression results for the HTMPTHG model.…”
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More Efficient Prediction for Ordinary Kriging to Solve a Problem in the Structure of Some Random Fields by Mohammad Mehdi Saber, Ramy Abdelhamid Aldallal

“…Although it is an unbiased estimator with a minimum mean-squared error, it does not necessarily have a minimum mean-squared error in the class of all linear estimators. …”
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