Study on the effect of humidity on coal mine dust concentration monitoring and its compensation strategy by ZHANG Anran

“…Results showed that the monitoring error of the humidity-compensated multi-angle light-scattering unit was ≤11.2%, a 2.9% reduction compared to the uncompensated unit, confirming the effectiveness of the compensation method.…”
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High-precision indoor localization in multi-level buildings by Chokri Ajroud, Jamel Hattay, Mohsen Machhout

“…By deploying multiple RFID readers across floors and constructing 3D holographic representations from signal phase data, our approach effectively distinguishes vertical positions, allowing for precise floor-specific tracking. The proposed method achieves an average localization error of approximately 5 cm, even in multifloor environments, through optimized reader placement and computational overhead reduction. …”
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A targeted one dimensional fully convolutional autoencoder network for intelligent compression of magnetic flux leakage data by Wenbo Xuan, Pengchao Chen, Rui Li, Fuxiang Wang, Kuan Fu, Zhitao Wen

“…Through practical experimental analysis, the reconstruction error such as MAE is reduced by about 27.7% and the compression ratio is improved by about 14% compared with traditional methods such as PCA. …”
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Enhancing Intermittent Spare Part Demand Forecasting: A Novel Ensemble Approach with Focal Loss and SMOTE by Saskia Puspa Kenaka, Andi Cakravastia, Anas Ma’ruf, Rully Tri Cahyono

“…The approach was empirically validated by comparing the model’s Mean Squared Error (MSE) performance and Area Under the Curve (AUC). …”
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Hybrid Spectrum Sensing Using Neural Network–Based MF and ED for Enhanced Detection in Rayleigh Channel by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…Extensive simulations demonstrate that the method achieves significant improvements in detection accuracy, false alarm reduction, and spectrum hole identification compared to traditional approaches. …”
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Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation by Ronglian Zhou, Di Di, Jun Li, Zhenglong Li

“…Validated against ERA5 and radiosonde observations, compared with the traditional Rt‐based method, the Ra‐based atmospheric profile retrievals show distinct improvements in boundary‐layer humidity retrieval with at least 20% error reduction. …”
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Research on dynamic modeling and control strategy of motor driven operating mechanism for 126 kV high voltage vacuum circuit breaker by Yifei Wang, Jianyuan Xu, Wei Li, Jinming Liu

“…Furthermore, comparative control experiments have been conducted in the motor-breaker integrated experimental platform to assess the reduction in the motor’s position tracking error, contact bouncing duration, and mechanical collision duration under the optimized motor control strategy. …”
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INVARIANT SYSTEM OF AUTOMATIC WATER-LEVEL REGULATING IN THE BOILER SHELL by G. T. Kulakov, A. N. Kuchorenko

“…The latter can be accomplished by means of massive reduction of the actuation-mechanism running time which depends directly on the regulator performance.The paper examines some foreign methods of PID-regulator adjusting in the cascade system of boiler-shell water-level automatic regulation. …”
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Coffee and tea consumption and glioma risk: a meta-analysis of cohort studies by Jinyu Pan, Chuan Shao, Hui Tang, Nan Wu

“…This study seeks to present a meta-analysis of the relationship between coffee and tea intake and glioma risk.MethodRelevant cohort studies that collected coffee and tea exposure prospectively were identified through searches of the PubMed, Embase, and Scopus databases. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…The results show that the proposed prediction model has a root mean square error reduction of about 78.25% and an increase of about 65.63% reliability compared with TCN.DiscussionThe model outperforms traditional methods in terms of accuracy and stability. …”
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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

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Joint learning equation of state surfaces with uncertainty-aware physically regularized neural networks by Dongyang Kuang, Shiwei Li, Buxuan Wang, Chao Xiong, Shichang Zhang, Yanyao Zhang

“…This result shows a significant improvement over the case without regularization, with an increase of 0.2 in $$R^2$$ and a reduction of 0.26 eV/atom in energy prediction error, and is even slightly better than the fully supervised case for traditional regression method based on the Mie-Gr $$\ddot{\text {u}}$$ neisen equation. …”
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Free Iron Determination in Soil by Flame Atomic Absorption Spectrometry by Sui’an ZHANG, Zhongrui YANG, Yuyu DUAN, Kaiqi YANG, Zhijie HU, Chun YANG, Sha HOU

“…The detection limit (3σ) of this method is 0.05g/kg, the quantification limit is 0.20g/kg, the linear correlation coefficient of the standard curve is 0.9995, the precision (RSD, n=6) is 1.95%−3.76%, and the standard error is less than 5%, which meets the analysis requirements of soil investigation. …”
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An Improved Wavelet Soft-Threshold Function Integrated with SVMD Dual-Parameter Joint Denoising for Ancient Building Deformation Monitoring by Jiaxing Zhao, Houzeng Han, Yang Deng, Youqiang Dong, Jian Wang, Wenjin Chen

“…SVMD-DP-IWT (sqtwolog) and SVMD-DP-IWT (minimaxi) effectively retain key vibration signal features during the denoising process. The proposed method significantly preserves vibration features during noise reduction of an ancient building in deformation monitoring, which is crucial for damage assessment.…”
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Integrated thermal and magnetic susceptibility modeling for air-motion artifact correction in proton resonance frequency shift thermometry by S. A. N. Nouwens, M. M. Paulides, J. Fölker, I. VilasBoas-Ribeiro, B. de Jager, W. P. M. H. Heemels

“…Thereto, we propose a new combined thermal and magnetic susceptibility model-based temperature estimation scheme that uses temperature estimates to improve the removal of air-motion-induced image artifacts. The method is experimentally validated using a dedicated phantom that enables the controlled injection of air-motion artifacts and with in vivo thermometry from a clinical hyperthermia treatment.Results We showed, using probe measurements in a heated phantom, that our method reduced the mean absolute error (MAE) by 58% compared to the state-of-the-art near a moving air volume. …”
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Forecasting regional carbon prices in china with a hybrid model based on quadratic decomposition and comprehensive feature screening. by Yaoyang Yi

“…The experimental results indicate that compared with the traditional model, the proposed model achieves average reductions of 67.30%, 47.68%, 48.42%, and 48.79% in the mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), respectively, demonstrating higher prediction accuracy and robustness. …”
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Investigation on the Role of Artificial Intelligence in Measurement System by P. A. Rezvy, Venkata Lakshmi Narayana Komanapalli

“…Soft computation using artificial neural networks and deep learning for linearization, compensation and error reduction, machine learning for estimation levaraging different algorithms like levenberg marquardt, scaled conjugate gradient, bayesian regularization, are assessed for training, testing and validation in real time and simulation. …”
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Filter-Based Feature Selection Using Information Theory and Binary Cuckoo Optimisation Algorithm by Ali Muhammad Usman, Umi Kalsom Yusof, Maziani Sabudin

“…Dimensionality reduction is among the data mining process that is used to reduce the noise and complexity of features in various datasets. …”
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Convolutional neural network-based deep learning for landslide susceptibility mapping in the Bakhtegan watershed by Li Feng, Maosheng Zhang, Yimin Mao, Hao Liu, Chuanbo Yang, Ying Dong, Yaser A. Nanehkaran

“…The CNN model outperformed other classification approaches, achieving an accuracy of 95.76% and a precision of 95.11%. Additionally, error metrics confirmed its reliability, with a mean absolute error (MAE) of 0.11864, mean squared error (MSE) of 0.18796, and root mean squared error (RMSE) of 0.18632. …”
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An Image and State Information-Based PINN with Attention Mechanisms for the Rapid Prediction of Aircraft Aerodynamic Characteristics by Yiduo Kan, Xiangdong Liu, Haikuo Liu

“…Extensive experiments validate the effectiveness of our model for rapid aircraft aerodynamic parameter prediction, achieving a significant reduction in prediction error that improves performance by 29.25% in RMSE and 37.99% in MRE compared to existing methods. …”
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