Wind speed forecasting approach using conformal prediction and feature importance selection by Cesar Vinicius Zuege, Stefano Frizzo Stefenon, Cristina Keiko Yamaguchi, Viviana Cocco Mariani, Gabriel Villarrubia Gonzalez, Leandro dos Santos Coelho

“…Taking into account a Beutenberg data set, Germany, the best model was Light Gradient Boosting Machine (LGBM)-VMD-SSA without partial fit, resulting in a root mean squared error (RMSE) criterion of 0.25031, coverage measure of 94.4%, and width measure of 1.008. …”
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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

“…Feature selection based on the Gini coefficient and Out-Of-Bag Error (OOBE) reduced the original 48 features to 23. …”
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A stochastic weather generator based framework for generating ensemble sub-monthly precipitation for streamflow prediction by Lu Yang, Jie Chen, Xunchang John Zhang, Lihua Xiong

“…New hydrological insights for the region: Results show that the numerical streamflow predictions exhibit a less accurate deterministic performance than the SWG-based framework with the climatology scheme over sub-monthly horizon, with leadtime-averaged mean absolute relative error dropping from 19.9 % to 8.3 %, and 21.8–11.1 % for Xiangjiang and Hanjiang river basins, respectively. …”
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A comprehensive evaluation of satellite-based and reanalysis soil moisture products over the upper Blue Nile Basin, Ethiopia by Addis A. Alaminie, Sofie Annys, Jan Nyssen, Mark R. Jury, Giriraj Amarnath, Muluneh A. Mekonnen, Seifu A. Tilahun

“…After applying bias correction, the Kolmogorov-Smirnov two-sample t-tests, Bonferroni correction, and statistical error metrics, the evaluation reveals that all products, except NASA-GLDAS, effectively capture soil moisture dynamics. …”
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Effects of insertion of an h-AlN monolayer spacer in Pt-WSe2-Pt field-effect transistors by Ken-Ming Lin, Po-Jiun Chen, Chih-Piao Chuu, Yu-Chang Chen

“…Abstract The growth of two-dimensional hexagonal aluminum nitride (h-AlN) on transition metal dichalcogenide (TMD) monolayers exhibits superior uniformity and smoothness compared to HfO $$_{2}$$ 2 on silicon substrate. …”
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DETERMINATION OF COORDINATES OF SEISMIC WAVE SOURCE BY AMPLITUDE METHOD OF PASSIVE LOCATION by Vasily D. Syten’ky

“…The value of the angle is taken into account when calculating the distance.For the seismic wave source located in the three-dimensional space, transition equations for combined coordinate systems (i.e. the Descartes (Cartesian)), at the axes of which the seismographs were placed, and the spherical coordinate systems were applied, and analytical equations were obtained for determination of coordinates, such as distance/polar radius, elevation angle/latitude, and bearing angle/longitude.To analyze the application of the radial basic method of passive location, an absolute error resulting from indirect measurement was calculated. …”
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Structure and microwave dielectric characteristics of (Ba,Sr,Ca)HfO3 ceramics by Xi Wang, Yi Han Ding, Xiao Li Zhu, Lei Li, Xiang Ming Chen

“…For Ba1–xSrxHfO3 and Sr1–yCayHfO3 with orthorhombic structures, the root mean square error between the calculated and measured τf was only 6.8 × 10−6 °C−1. …”
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Population Pharmacokinetic Modeling of the Oral Calcitonin Gene‐Related Peptide Receptor Antagonist Rimegepant in Adults by Craig M. Comisar, Jim H. Hughes, Jose Francis, Yorinao Chinda, Yamato Sano, Chieko Muto, Christine Neumar, Rajinder Bhardwaj, Richard Bertz, Jing Liu

“…Estimated typical values (%relative standard error) were apparent clearance (CL/F) = 24.1 L/h (4.86%), apparent central volume of distribution (Vc/F) = 114.0 L (5.36%), apparent inter‐compartmental clearance (Q/F) = 3.94 L/h (6.37%), apparent peripheral volume of distribution (Vp/F) = 46.0 L (5.30%), absorption rate constant (ka) = 3.86 h−1 (28.4%), and transit absorption rate constant (ktr) = 8.23 h−1 (8.24%). …”
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A Novel Approach to Generate Large-Scale InSAR-Derived Velocity Fields: Enhanced Mosaicking of Overlapping InSAR Data by Xupeng Liu, Guangyu Xu, Yaning Yi, Tengxu Zhang, Yuanping Xia

“…In some tracks, there are overlapping areas on the east and west sides, and the line-of-sight (LOS) value can be effectively corrected by using these overlapping areas with similar size for two cross-track mosaics. The root mean square error (RMSE) of these tracks was reduced by about 4% to 8% on average when verified using true values of GNSS data compared to no cross-track mosaic. …”
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Evaluation of the influence of hydrodynamic cavitation treatment of dark petroleum products on the yield of fractions with boiling points up to 400°C by B. V. Peshnev, E. V. Burlyaeva, V. B. Terenteva, D. V. Nikishin, A. I. Nikolaev, K. S. Andronov

“…The reduction of the anthropogenic burden on the environment is generally associated with the transition to alternative energy sources. However, some of these have only regional significance, while the effectiveness of others remains doubtful. …”
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Assessing groundwater drought in Iran using GRACE data and machine learning by Ali Kashani, Hamid R. Safavi

“…The Extreme Gradient Boosting (XGBoost) algorithm is employed for downscaling TWSA to a resolution of 0.25°, achieving a high Pearson correlation (R) of 0.99 and a root mean square error (RMSE) of 22 mm. The downscaled GWSA, derived from the balance equation, exhibits an average correlation (R) of 0.93 and RMSE of 39 mm with observational data. …”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…Specifically, it has been demonstrated to achieve a 22.6% reduction in root-mean-square error (RMSE) and a 16.7% decrease in training time when compared to traditional models. …”
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The Use of Neural Networks in Distance Education Technologies for the Identification of Students by O. A. Kozlova, A. A. Protasova

“…With an insufficient number of training sets (datasets), neural networks begin to perceive errors as reliable information, which, as a result, will lead to the need to retrain neural networks. …”
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External and internal drivers behind the formation, vegetation succession, and carbon balance of a subarctic fen margin by T. Juselius-Rajamäki, S. Piilo, S. Salminen-Paatero, E. Tuomaala, T. Virtanen, A. Korhola, A. Autio, H. Marttila, P. Ala-Aho, A. Lohila, A. Lohila, M. Väliranta

“…Thus, when estimating the peatland carbon stocks and predicting the future trajectories for peatland development, this heterogeneity should be taken into account to avoid errors caused by the oversimplification of peatland lateral expansion dynamics.…”
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TECTONOPHYSICAL SIGNS OF THE FORMATION OF STRONG EARTHQUAKE FOCI IN SEISMIC ZONES OF CENTRAL ASIA by S. I. Sherman

“…Earthquake predictions have errors as the current knowledge of focal mechanisms of strong (M≥8) earthquakes is still insufficient. …”
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BGP robustness testing based on RFSM by WANG Le-chun, ZHU Pei-dong, GONG Zheng-hu

“…Compared with the conformance test suite, robustness testing of BGP-4 （Border Gateway Protocol 4） shows that the error handling coverage of the negative test suite generated by this approach is increased by 54 percent, and the error-detecting capability is enhanced by 2.8 times.…”
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Motion Trajectory Control System for Production Line Robots Based on Variable Domain Fuzzy Control by Ling Pan

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DMP-PUNet: A novel network for two-dimensional InSAR phase unwrapping under severe noise and complex fringes conditions by Yu Chen, Shuai Wang, Yandong Gao, Yanjian Sun, Jinqi Zhao, Kun Tan, Peijun Du

“…For simulated data, DMP-PUNet achieved an overall average mean absolute error (MAE) in residuals of 0.221 rad, improving accuracy by 54.75 % with an average processing time of 0.81 s. …”
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The Deformation Monitoring Capability of Fucheng-1 Time-Series InSAR by Zhouhang Wu, Wenjun Zhang, Jialun Cai, Hongyao Xiang, Jing Fan, Xiaomeng Wang

“…Its deformation monitoring capability at the millimeter level was further validated through comparison with leveling measurements, with average errors and root mean square errors of 1.761 mm and 2.172 mm, respectively. …”
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Visual Automatic Localization Method Based on Multi-level Video Transformer by Qiping ZOU, Botao LI, Saian CHEN, Xi GUO, Taohong ZHANG

“…The system significantly reduces human error and enhances the consistency of output, which is crucial in high-precision manufacturing environments by automating the focus adjustment based on the clearest image. …”
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