Enhanced EKF and SVSF for state of charge estimation of Li‐ion battery in electric vehicle using a fuzzy parameters model by Meriem Ben Lazreg, Sabeur Jemmali, Bilal Manai, Mahmoud Hamouda

“…Moreover, the reduction of the maximum absolute error may reach 0.34% with the FP‐EKF, and 0.82% with the FP‐SVSF, compared to the same algorithms without the proposed FP method. …”
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Synchronous Control of a Dual-Motor Driving Rack and Pinion Module for Steer-by-Wire System by Insu Chung, Sehoon Oh, Kanghyun Nam

“…In order to improve these two goals, the existing synchronous control structures mainly designed controllers in the case of command tracking, and synchronization between motors used a compensation method using synchronous error. However, this method makes it difficult to analyze or control the level of synchronous error. …”
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Efficient Channel Prediction Technique Using AMC and Deep Learning Algorithm for 5G (NR) mMTC Devices by Vipin Sharma, Rajeev Kumar Arya, Sandeep Kumar

“…The estimation results are compared with the conventional minimum mean square error (MMSE) and an approximation to the linear MMSE (ALMMSE) method, which is obtained through channel state information (CSI). …”
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Advanced Machine Learning Approaches for Predicting Machining Performance in Orthogonal Cutting Process by Sabrina Al Bukhari, Salman Pervaiz

“…The analysis supports that the XGBoost model is the most accurate, with a 34.1% reduction in the mean squared error and a 17.1% reduction in the mean absolute error over these values for the Decision Tree. …”
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Active Vibration Control of Plate Partly Treated with ACLD Using Hybrid Control by Dongdong Zhang, Ling Zheng

“…A model reduction is completed by using iterative dynamic condensation and balance model reduction method to design an effective control system. …”
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Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning by Wangsong Xie

“…During the whole experiment, the time of the research method was less than 1.5 minutes. And for 1200 test samples, the average error of data risk prediction of the proposed method is 0.0217%. …”
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Active-Margin Transmission Power Control for Wireless Sensor Networks by Byung-Hee Son, Kwang-Jin Kim, Ye Li, Young-Wan Choi

“…The AM-TPC improves the reliability and reduces the power consumption, because it prevents unnecessary retransmission by reducing the number of error packets. By using the AM-TPC in mobile environments, we have experimentally obtained 28.3% reduction in current consumption when compared with using maximum power transmission.…”
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Research on a Surface Roughness Measurement Under ResNet-Based Roughness Classification and Light-Section With Seam-Driven Image Stitching (RCLS) by Huashen Guan, Qiushen Cai, Xiaobin Li, Guofu Sun

“…The experiments were conducted with vertical milled, planned, and turned samples that self-machined. The light section method had a reduction of 2.75% on the mean relative error compared to stylus and RCLS could further reduce the mean relative error by 1.42%, especially in planned sample. …”
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Enhanced Collaborative Filtering: Combining Autoencoder and Opposite User Inference to Solve Sparsity and Gray Sheep Issues by Lamyae El Youbi El Idrissi, Ismail Akharraz, Aziza El Ouaazizi, Abdelaziz Ahaitouf

“…Through experimental analysis of the MovieLens 100K dataset, we observe that our method achieves notable reductions in both RMSE (Root Mean Squared Error) and MAE (Mean Absolute Error), underscoring its superiority over the state-of-the-art collaborative filtering models.…”
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A Conceptual Investigation of a Large Radio Telescope Support Point Number Effect on Its Pointing Accuracy by Song Xue, Kaitong Ma, Congsi Wang, Peiyuan Lian, Yan Wang, Yuefei Yan, Qian Xu, Yuanpeng Zheng, Na Wang

“…Even though various compensation methods have been proposed to compensate for this pointing error, it remains as one of the challenges for the telescope pointing error reduction. …”
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Adapted Speed Control of Two-Stroke Engine with Propeller for Small UAVs Based on Scavenging Measurement and Modeling by Yifang Feng, Tao Chen, Qinwang Liu, Heng Zhao

“…The results indicate an 89% reduction in average speed error under varying air pressure and an 83.7% decrease in average speed overshoot in continuous step speed target experiments.…”
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Energy harvesting enhancement: A roadmap for systematically tuning controllers applied on synchronous generators of wind turbines by John Breno Santos Freitas, Felipe Augusto Silva Martins, Vinicius Foletto Montagner, Paulo Jefferson Dias de Oliveira Evald

“…Compared to the tenth algorithm in the rank, the ALO-based controller ensured a reduction of 96.78% and 90.27% of mean absolute error and root mean squared error, respectively. …”
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Optimization of the Backstepping Control Parameters of an Active Electrohydraulic Suspension to Improve Passenger Comfort and Road Handling by Rachid Fattah, Jean-Pierre Kenne, Khalid Benjelloun, Ahmed Chebak

“…Unlike conventional approaches relying on manual tuning or trial-and-error, our method systematically optimizes these parameters, ensuring a well-balanced trade-off between ride comfort and road handling. …”
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Hygroscopicity of ‘sucupira-branca’ (Pterodon emarginatus Vogel) fruits by Daniel E. C. de Oliveira, Osvaldo Resende, Lílian M. Costa, Glicélia P. Silva, Juliana de F. Sales

“…The models Chung-Pfost, Copace, Modified Halsey, Oswin Modified and Sigma Copace obtained high coefficient of determination (R2) and low chi-square (χ2), relative mean error (P) and estimated mean error (SE), and the Copace model was selected to represent the desorption isotherms. …”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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Remaining Useful Life Prediction of Rolling Bearings Based on an Improved U-Net and a Multi-Dimensional Hybrid Gated Attention Mechanism by Hengdi Wang, Aodi Shi

“…Experimental results from the IEEE PHM 2012 bearing dataset indicate that this method achieves a low mean root mean square error (RMSE = 0.0504) and mean absolute error (MAE = 0.0239). …”
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Large-Space Laser Tracking Attitude Combination Measurement Using Backpropagation Algorithm Based on Neighborhood Search by Ziyue Zhao, Zhi Xiong, Zhengnan Guo, Hao Zhang, Xiangyu Li, Zhongsheng Zhai, Weihu Zhou

“…Finally, the experimental platform is set up with the precision rotary table as the motion carrier to verify the effectiveness of the research method in this paper. The experimental results show that with the neighborhood-based backpropagation algorithm, the measurement results have a higher data update rate and a certain inhibition effect on the error accumulation of IMU. …”
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Speaker Model Clustering to Construct Background Models for Speaker Verification by Gökay DİŞKEN, Zekeriya TÜFEKCİ, Ulus ÇEVİK

“…The three-cluster model achieved the best performance with a 12.4% relative EER reduction in average, compared to the $i$-vector method. …”
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An Algorithm for Motion Estimation Based on the Interframe Difference Detection Function Model by Tengfei Zhang, Huijuan Kang

“…The basic theory of spatiotemporal context information and correlation filtering is studied to construct a fast target tracking method. The different computational schemes are designed for the flow of multiframe target detection from background removal to noise reduction, to single-frame detection, and finally to multiframe detection, respectively. …”
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