Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…Gas emission in the working face is influenced by a variety of factors. Dimensionality reduction methods, such as Principal Component Analysis, can reduce computational resources but may alter the original feature structure, leading to a loss of some detailed information in the dataset. …”
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Wireless Sensor Networks for Urban Development: A Study of Applications, Challenges, and Performance Metrics by Sheeja Rani S., Raafat Aburukba, Khaled El Fakih

“…Additionally, the proposed method obtains 36%, 30%, 46%, 35%, and 32% reduction in energy consumption, computation cost, execution time, error rate, and computational overhead, respectively, compared to conventional methods.…”
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Solar Wind Data Assimilation in an Operational Context: Use of Near‐Real‐Time Data and the Forecast Value of an L5 Monitor by Harriet Turner, Matthew Lang, Mathew Owens, Andy Smith, Pete Riley, Mike Marsh, Siegfried Gonzi

“…This suggests that an operational solar wind DA scheme would provide significant forecast improvement, with reduction in the mean absolute error of solar wind speed around 46% over forecasts without DA. …”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…The MLPNN monitors the mean squared error (MSE) and disruptive inputs throughout training and validation, revealing consistent MSE reduction over recovery periods. …”
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Effects of mindfulness meditation on human impulsivity: a systematic review and meta-analysis by Eric W. Tsang, Junling Gao, Chi Ngai Lo, Nicholas T. Trapp, Aaron D. Boes, Hinhung Sik

“…Neurophysiological findings showed a significant reduction in event-related potential amplitudes related to impulsivity, including N200, Error-Related Negativity (ERN), and P300 components (Cohen’s d = −0.65, 95% CI [−1.01, −0.08]). …”
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Assessing the Efficiency of Reduced Positional Games in Soccer: A Multivariate Analysis of Technical and Tactical Indicators According to Different Playing Systems by Mostafa Errama, Mustapha Bassiri, Jafaar Atifi, Said Lotfi

“…It seeks to determine how RPG optimize key indicators such as possession, passing, shooting, goals scored and error reduction, while exploring their influence on tactical synchronization and team cohesion. …”
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Participant motivators and perceptions of risks and benefits in adult Phase 2/3 COVID-19 vaccine clinical trials by Bettina Wunderlich, Brittany Feijoo, Rupali Limaye, Lawrence H. Moulton, Kawsar Talaat

“…While limited by low response rate and recall error, this study suggests that in future emergency situations, messaging should be prioritized to improve understanding of trials and vaccines.…”
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Multivariate forecasting of dengue infection in Bangladesh: evaluating the influence of data downscaling on machine learning predictive accuracy by Mahadee Al Mobin

“…Comparative analysis reveals that downscaling provided a $$28.5\%$$ 28.5 % improvement in accuracy and an $$89.3\%$$ 89.3 % reduction in mean absolute percentage error (MAPE) over non-downscaled data which has been proven to be statistically significant using the Wilcoxon signed rank test, illustrating the substantial advantages of employing downscaling for effective DENV forecasting. …”
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Evaluation of Hydropower Generation and Reservoir Operation under Climate Change from Kesem Reservoir, Ethiopia by Kinfe Bereda Mirani, Mesfin Amaru Ayele, Tarun Kumar Lohani, Tigistu Yisihak Ukumo

“…Bias, root mean square error, and coefficient of variation were used to check the accuracy of projected rainfall. …”
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Electromagnetic coil optimization for reduced Lorentz forces by Siena Hurwitz, Matt Landreman, Paul Huslage, Alan Kaptanoglu

“…The reduction of magnetic forces on electromagnetic coils is an important consideration in the design of high-field devices such as the stellarator or tokamak. …”
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A Piezoelectric Micromachined Ultrasonic Transducer-Based Bone Conduction Microphone System for Enhancing Speech Recognition Accuracy by Chongbin Liu, Xiangyang Wang, Jianbiao Xiao, Jun Zhou, Guoqiang Wu

“…Compared with the original noisy speech, the enhanced speech achieves a character error rate reduction of over 20%, approaching the speech recognition accuracy of clean speech. …”
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Machine Learning Techniques for Predicting Typhoon‐Induced Storm Surge Using a Hybrid Wind Field by Changyu Su, Bishnupriya Sahoo, Miaohua Mao, Meng Xia

“…ML is trained to overcome the residual error of the FVCOM, effectively reducing the inherent uncertainty of traditional methods. …”
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An adaptive sliding mode fault-tolerant control of variable speed reaching law for steer-by-wire systems by Jinwen Yang, Yinquan Yu, Dequan Zeng, Yiming Hu, Junhui Liu, Kai Liu, Giuseppe Carbone, Shaohua Luo, Xiaofeng Zhu

“…This paper focuses on actuator effectiveness reduction faults and establishes an analytical model of the SBW system that incorporates motor disturbances, steering feedback, and self-aligning torque characteristics. …”
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Intradialytic optical assessment of C-mannosyl tryptophan removal using spent dialysate by Joosep Paats, Annika Adoberg, Liisi Leis, Jürgen Arund, Kai Lauri, Merike Luman, Risto Tanner, Jana Holmar, Kristjan Pilt, Ivo Fridolin

“…The concentration of CMW in spent dialysate can be monitored based on spectrophotometric analysis of spent dialysate (r > 0.939, standard error: 0.07 μmol/L) and it is possible to evaluate CMW-based HD adequacy parameters, such as reduction ratio, mass of total removed solute, and TAC without blood sampling. …”
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Solar Radiation Pressure Modeling and Validation for BDS-3 MEO Satellites by Qiuli Chen, Xu Zhang, Chen Wang, Haihong Wang, Chen Ren, Fujian Ma, Xinglong Zhao

“…The orbit results, validated using satellite laser ranging (SLR) observations, show that the radial precision of approximately 3–4 cm can be achieved, with a reduction of the bias by up to 38% and a removal of the systematic error related to the Sun elongation angle in SLR residuals. …”
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An Advanced Generative AI-Based Anomaly Detection in IEC61850-Based Communication Messages in Smart Grids by Aydin Zaboli, Yong-Hwa Kim, Junho Hong

“…The proposed ToD model demonstrates significant advantages over the human-in-the-loop (HITL) approach, particularly in error rate, adaptability, and scalability. Specifically, compared to HITL, the ToD model achieves a reduction in false positives (FPs) of up to 20% and enhances the accuracy of AD by up to 17.5%, resulting in a general accuracy of 97.5%. …”
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A Novel Energy-Aware Approach for Locating Leaks in Water Pipeline Using a Wireless Sensor Network and Noisy Pressure Sensor Data by Muhammad Mysorewala, Muhammad Sabih, Lahouari Cheded, Mohammad Tariq Nasir, Muhammad Ismail

“…Using the DD strategy only, a noisy environment, and a small number of sensors, the performance of our scheme shows that, for small leak sizes, the estimation error in both leak location and size becomes unacceptably high. …”
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A Machine Learning-Based Intelligent Framework for Predicting Energy Efficiency in Next-Generation Residential Buildings by Hafiz Muhammad Shakeel, Shamaila Iram, Richard Hill, Hafiz Muhammad Athar Farid, Akbar Sheikh-Akbari, Farrukh Saleem

“…Further, machine learning models revealed that Random Forest, Gradient Boosting, XGBoost, and LightGBM deliver the lowest mean square error scores of 6.305, 6.023, 7.733, 5.477, and 5.575, respectively, and demonstrated the effectiveness of advanced algorithms in forecasting energy performance. …”
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Improving WRF-Chem PM2.5 predictions by combining data assimilation and deep-learning-based bias correction by Xingxing Ma, Hongnian Liu, Zhen Peng

“…Throughout the initial 24-h period, compared with the control experiment, the results of WRF-Chem_DA_BC (WRF-Chem_DA, WRF-Chem_BC) showed an improvement in terms of root-mean-square error, with reduction proportions varying from 38.90 % to 48.86 % (18.88 % to 32.44 %, 30.10 % to 46.08 %). …”
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Enhanced Spatiotemporal Landslide Displacement Prediction Using Dynamic Graph-Optimized GNSS Monitoring by Jiangfeng Li, Jiahao Qin, Kaimin Kang, Mingzhi Liang, Kunpeng Liu, Xiaohua Ding

“…The DCRNN-proposed model achieved the highest accuracy among eight competing models, recording a Root Mean Square Error (RMSE) of 2.773 mm in the Vertical direction, a 39.1% reduction compared to its baseline. …”
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