Spatial interpolation of cropland soil bulk density by increasing soil samples with filled missing values by Aiwen Li, Jinli Cheng, Dan Chen, Wendan Li, Yaruo Mao, Xinyi Chen, Bin Zhao, Wenjiao Shi, Tianxiang Yue, Qiquan Li

“…The RBFNN model, tailored for each sub-watershed, yielded the highest accuracy in filling missing BD, with an increase in coefficient of determination (R 2) by 19.54–37.36% and reductions in mean absolute error (MAE), mean relative error (MRE) and root mean square error (RMSE) by 8.91–14.81%, 9.02–16.22% and 7.71–13.61%, respectively. …”
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Prediction of Aluminum Alloy Surface Roughness Through Nanosecond Pulse Laser Assisted by Continuous Laser Paint Removal by Jingyi Li, Rongfan Liang, Han Li, Junjie Liu, Jingdong Sun

“…The SSA-BPNN model demonstrates high prediction accuracy, with a correlation coefficient (R²) of 0.98628, root mean square error (RMSE) of 0.024, mean absolute error (MAE) of 0.020 and mean absolute percentage error (MAPE) of 1.30% on the test set. …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…Key metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Percentage Error (MAPE), were employed to evaluate model performance. …”
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Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…The results show that, compared to other predictive models, the proposed model achieves reductions in Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) to 0.0002, 0.0159, and 0.0126, respectively, with the coefficient of determination (R2) increasing to 0.981. …”
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Are Junior Residents Accurate at Predicting Fetal Weight? An Analysis of Junior Residents' Performance of Estimated Fetal Weight Using Ultrasound and Leopold's Maneuver by Kimberly Huynh, Alicia Lunardhi, Karren Lewis, Trevor Pickering, Hindi E. Stohl

“…Maternal body mass index and actual BW were associated with absolute percentage estimation error. After adjusting for these variables, there was a statistically significant decrease in error between PGY1 and PGY2 for Leopold's method in term births; ultrasound (term and preterm) showed more modest reductions in error during PGY2. …”
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A wavelet-guided transformer approach for autofocus in brightfield biological microscopy by Wangka Yang, Meini Lv, Zhenming Yu, Jiawei Deng

“…Experiments conducted on a locally collected dataset demonstrate that WGT-Net achieves a mean absolute error (MAE) of 0.0869 and a root mean square error (RMSE) of 0.101, achieving 28.69% and 32.39% reductions in MAE and RMSE, respectively, compared with state-of-the-art methods, and completing predictions within milliseconds. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…Experimental results demonstrate that, compared to the traditional Gaussian Mixture Model approach, the proposed method improves trajectory accuracy by more than 15%, as shown by reductions in both the Mean Absolute Error and the Root Mean Square Error. …”
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Enhancing microgrid forecasting accuracy with a TCNN-TLS framework: A novel approach to mitigating uncertainty in renewable energy and load predictions by Md. Omer Faruque, Md. Majharul Islam, Md Jakaria Talukder, Arif Mia, Shahriar Tasnim, Md. Alamgir Hossain, S.M. Muyeen

“…The results demonstrate significant improvements after error adjustment, particularly in wind power and load forecasting, with notable reductions of 16.2% and 6.0% in RMSE and 17.4% and 5.7% in MAE, respectively. …”
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Multiplexed expansion revealing for imaging multiprotein nanostructures in healthy and diseased brain by Jinyoung Kang, Margaret E. Schroeder, Youngmi Lee, Chaitanya Kapoor, Eunah Yu, Tyler B. Tarr, Kat Titterton, Menglong Zeng, Demian Park, Emily Niederst, Donglai Wei, Guoping Feng, Edward S. Boyden

“…Across all datasets examined, multiExR exhibits a median round-to-round registration error of 39 nm, with a median registration error of 25 nm when the most stringent form of the protocol is used. …”
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Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data by S. Daenens, S. Daenens, S. Daenens, T. Verstraeten, T. Verstraeten, T. Verstraeten, P.-J. Daems, P.-J. Daems, A. Nowé, J. Helsen, J. Helsen, J. Helsen

“…The results show that both the spatial and the spatio-temporal GNN models outperform traditional data-driven power curve methods, achieving reductions in the mean absolute error (MAE) of approximately 22.6 % and 30.3 %, respectively, and in the mean absolute percentage error (MAPE) of around 20.7 % and 30.5 %, respectively. …”
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Study of Thermodynamic Horizontal Structure of the Middle and Upper Atmosphere Based on Atmospheric Detection Lidar Networks by Liting Ren, Yong Yang, Linmei Liu, Xin Lin, Jinzhou Zheng, Wei Wang, Jiaming Liang, Yuan Xia, Jiqin Wang, Kaijie Ji, Zhenwei Chen, Yuqi Zhang, Xuewu Cheng, Faquan Li

“…The assimilated temperature profiles closely match lidar observations, with the RMSE (root mean square error) of residual reductions of 67.35% at Urumqi, 60.69% at Yuzhong, and 34.80% at Yangbajing. …”
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Prediction of Carbonate Reservoir Porosity Based on CNN-BiLSTM-Transformer by Yingqiang Qi, Shuiliang Luo, Song Tang, Jifu Ruan, Da Gao, Qianqian Liu, Sheng Li

“…This model is applied to the Moxi gas field in the Sichuan Basin, using conventional logging curves as input feature variables for porosity prediction. Root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R²) are used as evaluation metrics for comprehensive analysis and comparison. …”
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Safety and efficacy of simultaneous photorefractive keratectomy and corneal cross-linking in managing suspected keratoconus by Ali Dal, Mehmet Canleblebici, Murat Erdağ

“…Eligibility criteria included stable refractive error for at least 1 year, spherical equivalent refractive error not exceeding −4.0 D, and central corneal thickness between 470 and 500 µm. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…In crop yield prediction, the proposed method achieves superior performance, as evidenced by reductions in both absolute error and mean squared error, along with attaining the highest R2 value (0.93). …”
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An Optimization Method for Indoor Pseudolites Anchor Layout Based on MG-MOPSO by Xiaohu Liang, Shuguo Pan, Shitong Du, Baoguo Yu, Shuang Li

“…Additionally, significant reductions are observed in average positioning error, maximum positioning error, and standard deviation across multiple test points. …”
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Enhancing energy management in battery electric vehicles: A novel approach based on fuzzy Q-learning controller by Salma Ariche, Zakaria Boulghasoul, Abdelhafid El Ouardi, Abdelhadi Elbacha, Abdelouahed Tajer, Stéphane Espié

“…The results show that the FQLC significantly outperforms the FLC, achieving MMAE values as low as 0.01, indicating substantial reductions in error rates. In the performed tests, the FQLC’s ability to manage energy use contributed to range extensions in certain cases, achieving an increase of up to 11 km. …”
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Prediction of Metabolic Parameters of Diabetic Patients Depending on Body Weight Variation Using Machine Learning Techniques by Oana Vîrgolici, Daniela Lixandru, Andrada Mihai, Diana Simona Ștefan, Cristian Guja, Horia Vîrgolici, Bogdana Virgolici

“…Model performance was evaluated using Mean Squared Error, Mean Absolute Error, and R² score. …”
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Precision‐Optimised Post‐Stroke Prognoses by Thomas M. H. Hope, Howard Bowman, Rachel M. Bruce, Alex P. Leff, Cathy J. Price

“…Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known. …”
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Investigating the accuracy of Apple Watch VO2 max measurements: A validation study. by Rory Lambe, Ben O'Grady, Maximus Baldwin, Cailbhe Doherty

“…Increased cardiorespiratory fitness is associated with reductions in coronary artery disease, diabetes and cancer. …”
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Controlling the energies of the single-rotor large wind turbine system using a new controller by Habib Benbouhenni, Nicu Bizon, Ilhami Colak, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…The proposed controller is designed using proportional, integral, and derivative error-based mechanisms, which fundamentally differ from traditional proportional-integral (PI) regulators. …”
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