Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA) by L. Terlinden-Ruhl, L. Terlinden-Ruhl, A. Couasnon, A. Couasnon, D. Eilander, D. Eilander, G. G. Hendrickx, P. Mares-Nasarre, J. A. Á. Antolínez

“…The proposed framework decreased the overall computational time by a factor of 4 and decreased the root mean square error in damages by a factor of 8. With a reduction in overall computational time and errors, additional stochastic variables such as the drivers' duration and time lag were included in the compound flood risk assessment. …”
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Research on Active Disturbance Rejection Control of Rigid–Flexible Coupled Constant Force Actuator by Chuanxing Jiang, Zhijun Yang, Jun Zheng, Bangshang Fu, Youdun Bai

“…Experimental results indicate enhanced performance compared to PID control: under dynamic disturbances, force deviations are limited to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>±</mo><mn>0.2</mn><mo> </mo><mi mathvariant="normal">N</mi></mrow></semantics></math></inline-formula> with a 98.5% reduction in mean absolute error, a 96.3% increase in settling speed, and 99% suppression of oscillations. …”
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Comparison of Molnupiravir Exposure‐Response Relationships for Virology Response and Mechanism of Action Biomarkers With Clinical Outcomes in Treatment of COVID‐19 by Akshita Chawla, Ruthie Birger, Brian M. Maas, Youfang Cao, Hong Wan, Julie Strizki, Arthur Fridman, Amanda Paschke, Carisa deAnda, Wei Gao, Matthew L. Rizk, Wendy Painter, Wayne Holman, Susanne Sardella, George Painter, Julie A. Stone

“…NHC incorporation in the SARS‐CoV‐2 RNA strand causes an accumulation of deleterious errors in the genome, resulting in reduced viral infectivity and replication. …”
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Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…When SOH is used to characterize battery life, significant errors will be introduced. In contrast, RUL will irreversibly decrease as the service time increases, which can provide a more reliable criterion for evaluation. …”
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Isotherms and thermodynamic properties of water adsorption in ‘Cumari-do-Pará’ pepper seeds by Karen C. Rodrigues, Hellismar W. da Silva, Isneider L. Silva, Samuel G. F. dos Santos, Daniel P. da Silva, Renato S. Rodovalho

“…The Chen-Clayton model is the one that best represents the water adsorption isotherms in ‘Cumari-do-Pará’ pepper seeds under the studied conditions, with 9.94% mean relative error, 0.40 mean estimated error and random distribution of residuals. …”
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SP-RF-ARIMA: A sparse random forest and ARIMA hybrid model for electric load forecasting by Kamran Hassanpouri Baesmat, Farhad Shokoohi, Zeinab Farrokhi

“…This methodology, termed SP-RF-ARIMA, is evaluated against existing approaches; it demonstrates more than 40% reduction in mean absolute error and root mean square error compared to the second-best method.…”
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Enhanced SOC estimation method for lithium-ion batteries using Bayesian-optimized TCN–LSTM neural networks by Taotao Hu, Xiting Zhu, Maokai Tian

“…Experimental results demonstrate the effectiveness of the proposed method, achieving a coefficient of determination (R2) of 0.996, a mean absolute error of 0.146%, and a root mean square error of 0.207%. …”
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Radiative heat and mass transfer significance through a permeable vertical plate with rotational effects: An artificial approach using the Levenberg–Marquardt algorithm by R. Kavitha, Kavikumar Jacob, Ahmad Haji Zadeh, Nagarajan Deivanayagampillai

“…Model accuracy is validated through mean squared error graphs, regression analysis, and error histograms, demonstrating reliable fluid dynamics predictions under varying conditions.…”
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Analysis of corn price forecast in China based on Lasso-XGBoost-SHAP by Wenming Cheng, Fangyuan Li

“…Results demonstrate that the Lasso-XGBoost model outperforms traditional linear models (LM) and other algorithms, including SVM (Support Vector Machine) and MLP (Multilayer Perceptron), with root mean squared error (RMSE) of 0.094, coefficient of determination (R2) of 0.973, mean absolute error (MAE) of 0.072, representing a 7.84% reduction in RMSE compared to standalone XGBoost. …”
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Spoofing Evident and Spoofing Deterrent Localization Using Ultrawideband (UWB) Active&#x2013;Passive Ranging by Haige Chen, Ashutosh Dhekne

“…Our experimental evaluation shows a 30-cm <inline-formula><tex-math notation="LaTeX">$\text {75}{\text{th}}$</tex-math></inline-formula> percentile error for ToF-based honest tag localization and a submeter error for TDoA-based localization for spoofing tags. …”
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An Algorithm for Simplifying 3D Building Models with Consideration for Detailed Features and Topological Structure by Zhenglin Li, Zhanjie Zhao, Wujun Gao, Li Jiao

“…Compared to the QEM algorithm and the other two comparison algorithms selected in this paper, the simplified model resulting from this algorithm exhibit a reduction in Hausdorff distance, mean error, and mean square error to varying degrees. …”
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A Sparse CoSaMP Channel Estimation Algorithm With Adaptive Variable Step Size for an OFDM System by Ning Xiaoling, Chen Yangyi, Zhang Linsen

“…Additionally, the proposed algorithm was superior over the SAMP algorithm in terms of reconstruction, mean square error (MSE), and bit error ratio (BER).…”
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A Hybrid Learning Framework for Enhancing Bridge Damage Prediction by Amal Abdulbaqi Maryoosh, Saeid Pashazadeh, Pedram Salehpour

“…The proposed model demonstrates exceptional performance, achieving accuracy rates ranging from 98.27% to 100%, with error rates between 1.73% and 0% across multiple bridge damage datasets. …”
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A modification design method for the angular misalignment of the spline drum shaping by YUAN Xichuan, LIU Qi, TANG Jinyuan, LI Yuan, SU Hui

“…Finite element simulation and test verification were subsequently conducted to validate the accuracy and effectiveness of this method.ResultsThe analytical results demonstrate that regarding computational efficiency, the proposed method reduces finite element simulations from 6-10 iterations required by traditional trial-and-error approaches to a single simulation for determining optimal modification, achieving over 80% efficiency improvement; in performance enhancement, the optimized modification demonstrates 30.22% reduction in contact stress and 50% decrease in maximum tooth wear volume under misalignment conditions, effectively eliminating edge contact while significantly extending service life.…”
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Time-of-flight-based advanced surface reconstruction methods for real-time volume estimation of bulk harvested wild blueberries by Connor C. Mullins, Travis J. Esau, Qamar U. Zaman, Ahmad A. Al-Mallahi, Aitazaz A. Farooque, Craig B. MacEachern

“…Convex hull exhibited the highest initial MAE (0.0495 ± 0.0235 m³) but showed significant error reduction post-bias correction (to 0.0122 ± 0.0128 m³), leading to a reduced variability. …”
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Framework for Integrating Requirements Engineering and DevOps Practices in Robotic Process Automation with a Focus on Optimizing Human–Computer Interaction by Leonel Patrício, Leonilde Varela, Zilda Silveira

“…Key results include an 83% reduction in processing time, an 81.25% decrease in error rates, and an 80% reduction in manual tasks, alongside improved compliance and scalability. …”
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Forgery Detection in Dynamic Signature Verification by Entailing Principal Component Analysis by Shohel Sayeed, S. Andrews, Rosli Besar, Loo Chu Kiong

“…Calculation of the sum of mean squares of Euclidean distance has been used to project the advantage of our proposed method. 3.1% and 7.5% of equal error rates for 14 and 5 channels further reiterate the effectiveness of this technique.…”
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The Treatment of Hospital Wasterwater Electrocoagulation Using Iron Electrodes: Analysis by Response Surface Methodology by Darmadi M. Yusuf, Mirna Rahmah Lubis, Adisalamun Adisalamun

“…The reduction percentage is TSS 72.45%.…”
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Channel estimation method of massive MIMO-OFDM system based on adaptive compressed sensing by Yiyang HU, Lina QI

“…Massive multiple-input multiple-output (MIMO) is a solution for efficiently providing connection services for a variety of machine equipment in the Internet of things (IoT), and efficient connection services require accurate channel estimation.Aimed at the problems of high pilot overhead and poor performance of normalized mean square error (NMSE) estimation in downlink channel estimation of massive MIMO systems, based on the compressed sensing (CS) theory, the common sparsity of the channel space domain was combined while using the feature of lower sparsity of adjacent time slot differential channel impulse response (CIR), which leaded to a significant reduction in pilot overhead.In the reconstruction algorithm, a two-stage differential estimation algorithm, which divided the channel estimation in consecutive time slots with time correlation into two stages, was proposed and the idea of adaptive compressed sensing was combined to achieve fast and accurate CIR estimate.The simulation results show that the proposed two-stage differential channel estimation algorithm not only has a significant improvement in the estimated NMSE performance and data transmission rate compared to the existing CS-based multiple measurement vector (MMV) algorithm, but also show a certain reduction in runtime complexity.…”
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Determination of the Shortest Hamiltonian Paths in an Arbitrary Graph of Distributed Databases by E. G. Andrianova, V. K. Raev, D. I. Filgus

“…A method has been developed for finding the shortest Hamiltonian path in an arbitrary graph based on the rank approach, which provides high efficiency and a significant reduction in the error in solving the problem of organizing the process of managing multiple transactions and queries when they are implemented in network databases. …”
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