Advanced Numerical Validation of Integrated Electrochemical-Thermal Models for PCM-Based Li-Ion Battery Thermal Management System by Mahdieh Nasiri, Hamid Hadim

“…Incorporating Capric acid (with a phase transition range of 302–305 K) as the PCM, the thermal management model demonstrates significantly improved accuracy over existing models in the literature. Notable error reductions include a 78.3% decrease in the Mean Squared Error (0.477 vs. 2.202), a 53.4% reduction in the Root Mean Squared Error (0.619 vs. 1.483), and a 55.5% drop in the Mean Absolute Percentage Error. …”
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UWB Indoor Localization Based on Artificial Rabbit Optimization Algorithm and BP Neural Network by Chaochuan Jia, Can Tao, Ting Yang, Maosheng Fu, Xiancun Zhou, Zhendong Huang

“…In LOS conditions, the ARO-BP model achieves a localization error of 6.29 cm, representing a 49.48% reduction compared to the 12.45 cm error of the standard BPNN. …”
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Benefits of electronic charts in intensive care and during a world health pandemic: advantages of the technology age by Simon Ball, Felicity Evison, Laurie Lucas, Tanya Pankhurst, Richard Baker, Suzy Gallier, Jamie J Coleman, Ian Young, Anwar Shah, Steve Ryan, Helen Gyves, David Rosser, Chris Ragdale, Louise Denner, Laura Rathbone, Deborah McKee, Jolene Atia, Mark Garrick

“…This was an extension to the existing hospital wide digital health system. We evaluated error reduction, time-savings and the costs associated with conversion from paper to digital records. …”
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Understanding the environmental health implications of tourism on carbon emissions in China by Jinhua Shao, Sheng Fang, Meiling Zhao, Wanxin Qian, Cai Wang

“…Studying the impact of China’s tourism industry on carbon emissions is of great significance in scientifically formulating emission reduction policies and helping China to realize its carbon reduction goals. …”
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Stress and strength analysis of aluminum alloy structures under the effect of thermal and mechanical force by HE Zhiquan, QIU Huihui, SUN Yuheng, GUO Yujie, WEI Xiaohui

“…Therefore, considering the reduction effect of temperature on material parameters can establish a more accurate model for predicting structural strength. …”
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Learning to rank quantum circuits for hardware-optimized performance enhancement by Gavin S. Hartnett, Aaron Barbosa, Pranav S. Mundada, Michael Hush, Michael J. Biercuk, Yuval Baum

“…In particular, we find that our best model leads to a $1.8\times$ reduction in selection error when compared to the baseline approach and a $3.2\times$ reduction when compared to random selection. …”
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Improving prediction accuracy in agricultural markets through the CIMA-AttGRU model. by Yankun Jiang, Jinhui Liu, Xiaotuan Li

“…Our empirical results demonstrate a significant improvement in forecasting precision, with the CIMA-AttGRU model achieving a Mean Absolute Error (MAE) reduction of 15% and a Mean Squared Error (MSE) reduction of 20% compared to conventional models. …”
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Enhancing Supply Chain Efficiency Resilience Using Predictive Analytics and Computational Intelligence Techniques by Lixing Bo, Jie Xu

“…The Transformer model achieved a reduction in Mean Absolute Error (MAE) from 15.8 to 8.2 and Root Mean Squared Error (RMSE) from 22.3 to 11.5, demonstrating enhanced forecasting accuracy. …”
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Examining the Complementarity of GEO and LEO Hyperspectral Infrared Sounders for NWP by Erica L. McGrath‐Spangler, N. C. Privé, Bryan M. Karpowicz, Andrew K. Heidinger, Min‐Jeong Kim, Satya Kalluri

“…Results show that LEO sounders are crucial in the reduction of global errors, but that high temporal resolution observations are critical on the scale of targeted regions. …”
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Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

“…Results show that the LSTM-RUNAO model outperformed conventional ANN methods, achieving a 28.7% reduction in root mean square error (RMSE) and a 20.3% reduction in mean absolute error (MAE) compared to standard ANN models. …”
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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…Abstract Experimental results show that the algorithm converges faster and has a smaller average error compared to the BP algorithm and the attribute reduction algorithm. …”
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Investigation of the impact of token embeddings in Transformer-based models on short-term tropical cyclone track and intensity predictions by Yuan-Jiang Zeng, Yi-Qing Ni, Zheng-Wei Chen, Guang-Zhi Zeng, Jia-Yao Wang, Pak-Wai Chan

“…Comparative analysis with four recurrent neural network (RNN) models demonstrates the superiority of the refined Transformer models over RNNs: iTransformer reduces mean absolute error (MAE) and root mean square error (RMSE) by 29.55% and 25.80% (latitude), 50.31% and 46.18% (longitude), 8.71% and 9.98% (pressure), and 8.68% and 9.45% (wind speed), while TVFormer achieves MAE and RMSE reductions of 13.98% and 13.84% (latitude), 39.11% and 38.02% (longitude), 13.69% and 14.02% (pressure), and 12.84% and 12.94% (wind speed) on average. …”
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Personalized prediction model generated with machine learning for kidney function one year after living kidney donation by Rikako Oki, Toshihio Hirai, Kazuhiro Iwadoh, Yu Kijima, Hiroyuki Hashimoto, Yasunori Nishimura, Taro Banno, Kohei Unagami, Kazuya Omoto, Tomokazu Shimizu, Junichi Hoshino, Toshio Takagi, Hideki Ishida, Toshihito Hirai

“…Abstract Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. …”
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差动丝杠机构的传动性能 by 陈曼龙

“…As a new transmission parts,Differential Roller Screw（DRS）has great reduction ratio.Through introducing principle of this screw and analyzing its motion performance,the parameter affected DRS’s motion characteristic is discussed and the equation of DRS’s motion relation is deduced.And the DRS ’s efficiency and transmission error are investigated.…”
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Obliczanie Sił Krytycznych dla Sprężystych Prętów Niepryzmatycznych Metoda Interpolacji Częściowej by M. Życzkowski

“…This enables a considerable reduction of the final interpolation error ba(x). The paper gives an example of the evaluation of the error for the ordinary and the accelerated partial interpolations Eqs. (8.17) and (8.21), respectively and presents formulae for the coefficients of basic approximations assumed in the form of a polynomial, (9.3), (9.7), and (9.9). …”
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Development and Evaluation of a LiFi-Transceiver Module for TMTC Intra-Satellite Communication by Marek Jahnke, Benjamin Palmer, Ulf Kulau

“…The use of Light Fidelity (LiFi) can enable the reduction of satellite mass by reducing the wiring harness while avoiding electromagnetic interference. …”
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Improving Precision and Reducing Runtime of Microscopic Traffic Simulators through Stratified Sampling by Khewal Bhupendra Kesur

“…LHS is found to outperform AV, and reductions of up to 71% in the standard error of estimates of traffic network performance relative to independent sampling are obtained. …”
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Image Denoise based on Undecimated Wavelet Transform: A Comparative Analysis by Israa Hashim Latif

“…The initial section examined the performance of Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) utilizing MATLAB, indicating that biorthogonal wavelets provide optimal noise reduction with minimal degradation of detail. …”
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Learned Shrinkage Approach for Low-Dose Reconstruction in Computed Tomography by Joseph Shtok, Michael Elad, Michael Zibulevsky

“…The optimization is performed with respect to an error functional in the image domain that combines the mean square error with a gradient-based penalty, promoting image sharpness. …”
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NUMERICAL METHOD FOR ESTIMATION OF TENSILE LOAD IN TIE-RODS by Kseniia Riabova, Luca Collini, Rinaldo Garziera

“…Qualitative analysis of the results showed a significant reduction of the error compared to models with different boundary conditions. …”
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