Numerical investigation of flow field characteristics over vertical drops with sudden contraction for different contraction ratios by Hossein Shahin, Afshin Eghbalzadeh, Mitra Javan

“…The computational model was validated against experimental data, yielding acceptable levels of accuracy based on average percentage error (APE) and root mean square error (RMSE) metrics. …”
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FBG‐driven simulation for virtual augmentation of fluoroscopic images during endovascular interventions by Valentina Scarponi, Juan Verde, Nazim Haouchine, Michel Duprez, Florent Nageotte, Stéphane Cotin

“…This system demonstrated accurate prediction with a mean 3D error of 2.4 ± 1.3 mm and a mean error of 1.1 ± 0.7 mm on the fluoroscopic image plane between the real catheter shape after guidewire withdrawal and the predicted shape. …”
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Medium-Term Hourly Electricity Tariff Forecasting Using Ensemble Models by Matrenin P.V., Arestova A.Yu., Antonenkov D.V.

“…The most significant results are the proof of the possibility of obtaining the month ahead electricity tariff rate forecast with the mean absolute percentage error 4 %. It could be used for electricity costs reduction by regulating the load curve. …”
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Adapted Speed Control of Two-Stroke Engine with Propeller for Small UAVs Based on Scavenging Measurement and Modeling by Yifang Feng, Tao Chen, Qinwang Liu, Heng Zhao

“…The results indicate an 89% reduction in average speed error under varying air pressure and an 83.7% decrease in average speed overshoot in continuous step speed target experiments.…”
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Research and validation of forest carbon sequestration measurement model based on biomass method-A case study of Guizhou Province. by Zhang Min, Wu Yang, Qiu Yan, Yan Jun, Li Chunling, Ran Wen Rui

“…With the establishment of China Certified Voluntary Emission Reduction (CCER) market, more and more people pay attention to the development of forestry carbon sequestration in Guizhou. …”
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Red Fox Optimization-Based Estimation Algorithms for Splitting Tensile Strength of Basalt Fiber Reinforced Concrete by Xiao Wu, Daoyong Zhu, Qin Yan

“…Also, the models’ results indicate that RFORF outperforms another model, with −34% lower values in symmetric mean absolute percentage error (SMAPE) and a significant −80% reduction in mean squared logarithmic error (MSLE). …”
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Construction of a NOx Emission Prediction Model for Hybrid Electric Buses Based on Two-Layer Stacking Ensemble Learning by Jiangyan Qi, Xionghui Zou, Ren He

“…The evaluation metrics of the proposed model—mean absolute error, root mean square error, and coefficient of determination—are 0.0068, 0.0283, and 0.9559, respectively, demonstrating a significant advantage compared to other benchmark models.…”
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Estimation of Ambient Air PM2.5 Concentration Using MLP and RBF by Ali Mohammadi Bardshahi, Nematollah Jaafarzadeh, Tayebeh Tayebeh, Fazel Amiri

“…The dataset was divided into three subsets: 70% for training, 15% for testing, and 15% for validation.Results: The results showed that the average concentration of PM2.5 was 26.5 μg/m3. The root mean square error (RMSE) was estimated as 6.49 μg/m3. Increasing the input data resulted in a slight reduction in network error, with the RBF model, utilizing 1450 inputs and an RMSE of 6.47, achieving the same accuracy as the MLP model with 10 inputs.Conclusion: Given that the PM2.5 concentration estimates from the RBF and MLP models deviated by less than 23 and 25%, respectively, compared to the observed concentrations, both MLP and RBF can be regarded as reliable tools for predicting PM2.5 levels.…”
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GDSMOTE: A Novel Synthetic Oversampling Method for High-Dimensional Imbalanced Financial Data by Libin Hu, Yunfeng Zhang

“…The failure of distance measurement in high-dimensional space, error accumulation caused by noise samples, and the reduction of recognition accuracy of majority samples caused by the distribution of synthetic samples are the main reasons that limit the performance of current methods. …”
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Silent speech recognition using visual cascading fusion of tongue-lip movements based on pre-trained and fine-tuned model by Chongchong Yu, Xuening Wang, Zhaopeng Qian

“…Experimental results show that the average word error rate (WER) of proposed model can achieve to 23.34%, representing a 1.75% reduction compared to the baseline model. …”
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Residual learning based convolution neural network for improved channel estimation for VehA channel by Sunita Khichar, Yahui Meng, Abhishek Sharma, Muhammad Saadi, Amir Parniarifard, Sushank Chaudhary

“…Traditional channel estimation techniques, such as least squares (LS) and linear minimum mean square error (LMMSE), face limitations in terms of estimation accuracy and computational complexity. …”
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An Improvement of the Load Transfer Method for Energy Piles Under Thermo-Mechanical Loads by Haofan Yang, Haowen Pan, Chenfeng Zong, Ziyi Wang, Gang Jiang

“…The calculated results at the pile head show an 18% reduction in error compared to previous studies. The average error compared with field test results is within 20%, with consistent trend patterns, confirming the feasibility of the proposed method. …”
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Smooth Guided Adversarial Fully Test-Time Adaptation by Dong Li, Panfei Yang

“…Experimentally, SAFTTA demonstrates state-of-the-art results, improving error rate by 0.7% on the CIFAR-10-C benchmark and achieving a 1.1% reduction in error rate on the ImageNet-C benchmark compared to existing methods. …”
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Temperature-Influenced SOC Estimation of LiFePO₄ Batteries in Hybrid Electric Tractors Based on SAO-LSTM Model by Yiwei Wu, Xiaohui Liu, Jingyun Zhang, Mengnan Liu, Lin Wang, Xiaoxiao Du, Xianghai Yan

“…The proposed SAO-LSTM model demonstrated superior SOC estimation performance compared to traditional ampere-hour integration, achieving a 98.23% error reduction. Evaluation results showed 0.39% and 0.31% decreases in root mean square error and mean absolute error, respectively, confirming the model’s robustness and high estimation accuracy for LiFePO₄ batteries in hybrid electric tractors.…”
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ALS+PDR: Indoor Pedestrian Dead Reckoning Using a Smartphone Ambient Light Sensor by Sosuke Otsuka, Yusei Onishi, Mananari Nakamura, Hiromichi Hashizume, Masanori Sugimoto

“…The results indicated an average error of 11.30 m when only PDR was used, with a substantial reduction to 2.03 m when the proposed method was used. …”
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Optimal Design of High-Precision Focusing Mechanism Based on Flexible Hinge by Zhanwei Huo, Guangzhen Li, Luyang Tan, Tianwen Yang, Dapeng Tian, Ji Li

“…This study indicates that the inclusion of a flexible hinge in the focusing mechanism leads to a substantial decrease in tilt error.…”
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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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Machine Learning-Based Lithium Battery State of Health Prediction Research by Kun Li, Xinling Chen

“…The models were validated using the NASA PCoE battery aging datasets B0005, B0006, and B0007, with prediction accuracy evaluated based on Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R²). …”
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Rolling Prediction of Emergency Supplies Based on Postdisaster Multisource Time-Varying Information by Wei Li, Ming Zhang, Boquan Li, Songrui Li, Zhifeng Qiu

“…Finally, the proposed method is verified by an experiment with a general mean prediction error of 10.96%. However, the general mean prediction error of SVM reaches 17.77% in the static multistep prediction. …”
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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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