Label Noise Robust Crowd Counting with Loss Filtering Factor by Zhengmeng Xu, Hai Lin, Yufeng Chen, Yanli Li

“…Our extensive experiments demonstrate the effectiveness of LNRCC, which consistently improves performance across all models and datasets, with an average enhancement of 3.68% in Mean Absolute Error (MAE), 6.7% in Mean Squared Error (MSE) and 4.68% in Grid Average Mean Absolute Error (GAME). …”
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A novel mixed technique for order abatement in linear time invariant systems and robustness analysis of DC motor by Priyajit Dash, M. L. Meena, M. Ramkumar Raja, Wahaj Ahmad Khan

“…The Integral of squared error (ISE) is employed as the objective function to minimize the error between the high-order system (HOS) and the AS, ensuring accurate coefficient estimation. …”
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Indoor Air Wellness: A Predictive Model for Pollution Control Using Advanced AI Techniques by Kalyan Chatterjee, Muntha Raju, Bhoomeshwar Bala, U. Nikitha, Gampala Prabhas, Naim Ahmad, Ayman Qahmash, Wade Ghribi, Bernardo Lemos, Saurav Mallik

“…The model excels in dynamic environments by refining the accuracy of the proposed Kal-ANN algorithm achieving a predictive accuracy of up to 96. 55%, a root mean square error, a Mean Absolute Error, and a Mean Squared Prediction Error as low as 9.85, 6.12, and <inline-formula> <tex-math notation="LaTeX">$3.15~g/m$ </tex-math></inline-formula>. …”
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Optimal strategy for improved estimation of population mean of sensitive variable using non-sensitive auxiliary variable by Abdullah A. Zaagan, Dinesh K. Sharma, Ali M. Mahnashi, Mutum Zico Meetei, Subhash Kumar Yadav, Aakriti Sharma, Pranav Sharma

“…For a wide range of sensitive research applications, it is advisable to choose an estimator that possesses desirable sample properties and a minimized mean squared error (MSE).…”
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Rapid identification method of milk powder from different animals based on Raman spectroscopy by Xinyue Zhang, Qiaoling Yang, Shuqing Gu, Yongai Yu, Xiaojun Deng, Bing Niu, Qin Chen

“…Furthermore, the quantitative models based on partial least squares regression and support vector machine regression exhibited excellent linear correlations, with both root mean square error and mean relative error below 0.2. These models successfully quantified adulteration in camel, mare, and donkey milk powders in comparison to goat and cow milk powders. …”
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LSTM-Based State-of-Charge Estimation and User Interface Development for Lithium-Ion Battery Management by Abdellah Benallal, Nawal Cheggaga, Amine Hebib, Adrian Ilinca

“…The proposed framework demonstrates superior prediction accuracy, achieving a Mean Square Error (MSE) of 0.0023 and a Mean Absolute Error (MAE) of 0.0043, outperforming traditional estimation methods. …”
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Control System for U-Arm Robot Arm Movement with Linear Gripper Based on Inverse Kinematic Method by Aditya Putra Perdana Prasetyo, Ikang Rahmatullah, Kemahyanto Exaudi, Rendyansyah Rendyansyah

“…Testing results indicate an average coordinate error of 7.13%, demonstrating the system's precision and reliability. …”
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The control effect of the pore and fracture characteristics of tectonic coal assisted by the triaxial stress permeability system on permeability by Shi wenfang, Ru zhongliang, Zhao binbin, Lu guoju

“…Moreover, the proposed ShuffleNet V2-Bidirectional Gated Recurrent Unit-Graph Attention Mechanism model demonstrates superior performance compared to existing models, achieving an accuracy of 95.62%, a root mean square error of 4.19, and a mean absolute error of 8.13. …”
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Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

“…The models were evaluated using different metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), R², Root Mean Squared Error(RMSE) and Normalized Root Mean Squared Error(NRMSE), with visual analyses through scatter plots and time series plots. …”
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An Algorithm for the Solution of Integro-Fractional Differential Equations with a Generalized Symmetric Singular Kernel by Sameeha A. Raad, Mohammed A. Abdou

“…In combination with the solution rules, the convergence of the solution is studied, and the error equation resulting from the solution is a stable error-integral influencer equation. …”
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Prediction of Traction Energy Consumption for Urban Rail Transit Trains in Relative Speed Mode by GUO Tuansheng

“…The prediction accuracy ranges from 92.0% to 99.6%, with a maximum relative error of 2.36%, an average relative error of 1.75%, and a root mean square relative error of 1.52%, outperforming other prediction methods by every indicator value. …”
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Monthly Water Level Prediction Based on ESMD-VMD-ESN Hybrid Model by LI Ang, ZHANG Kun, SANG Yuting, BI Wan

“…Water level sequence contain complex features of multiple frequency information.To improve the prediction accuracy of the water level sequences,a combined model was developed based on Extreme-point Symmetric Mode Decomposition (ESMD),Variational Mode Decomposition (VMD) and Echo State Network (ESN),namely ESMD-VMD-ESN.And it was applied to forecast water level of the Taipuzha station in the upper reaches of Taipu River.The predictive effect of the “first decomposition-second decomposition-prediction-reconstruction” model was explored by comparing it with a single model ESN and the combination model ESMD-ESN.The results show that ESMD-VMD-ESN has the highest accuracy,followed by ESMD-ESN,and the lowest ESN accuracy.Compared with the ESN,the Willmott's Index of Agreement (WIA) and Pearson Correlation Coefficient (PCC) of ESMD-ESN respectively increased by 51% and 11%,the Mean Absolute Error (MAE) and Root Mean Squard Error (RMSE) of ESMD-ESN respectively decreased by 14% and 45%.ESMD can effectively simplify the water level sequence and reduce the prediction error.Compared with the ESMD-ESN,the WIA and PCC of ESMD-VMD-ESN respectively increased by 5% and 10%,the MAE and RMSE of ESMD-ESN respectively decreased by 52% and 50%.VMD can further simplify the highest frequency component of ESMD and improving the model prediction accuracy.In conclusion,the combined model ESMD-VMD-ESN has well applicability and stability in the monthly water level prediction.…”
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Sparse Probabilistic Synthesis of Quantum Operations by Bálint Koczor

“…The approach is very general and a broad spectrum of practical applications in quantum technologies are explicitly demonstrated.…”
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Introduction of modified root finding approaches and their comparative study with existing methods by Haputhanthrige Hashintha Dilan Kumara, Samoshi Shanika, Haputhanthrige Sachithra Gayashani, Withanage Ujitha Imeshan, Sanjula Thilakarathne

“…Furthermore, we illustrate some numerical applications to discuss error analysis, convergence analysis, and comparisons with existing methods. …”
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Generalized Additive Model for Predicting ECBR of Stabilized Subgrades for Pavement by Alka Shah, Tejaskumar Thaker, Vipin Shukla

“…The Bivariate GAM model demonstrated superior performance, achieving a cross-validation mean squared error of <inline-formula> <tex-math notation="LaTeX">$9.2203\times 10^{-5}$ </tex-math></inline-formula>, mean absolute error (MAE) of 0.007, root mean squared error (RMSE) of 0.009, mean absolute percentage error (MAPE) of 0.077 and percentage bias (PBIAS) of 0.00026% indicating minimal deviation and high accuracy. …”
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Scalable Behavioral Authentication by Md Morshedul Islam, Reihaneh Safavi-Naini, Marc Kneppers

“…We use extensive experiments to validate the above, including the increase in the verification error with the increase in the database size, and implement and evaluate our proposed scalable verification algorithm in reducing this error. …”
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An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion by Yicen Liu, Songhai Fan

“…For this reason, in this paper, 3D Lidar information and visual information are fused to create a SLAM algorithm applicable to substation inspection robots to solve the above laser SLAM localization error problem and improve the algorithm’s localization accuracy. …”
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A DNN-based 5G MIMO system adopting a mix of tactics by Md. Matiqul Islam, Md. Ashraful Islam, Md. Firoz Ahmed

“…The proposed system employs a linear minimum mean square error (LMMSE) equalizer to ensure effective signal detection. …”
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Modified Local Regression for Signal Resampling by Reiner Jedermann, Yogesh Kapoor, Walter Lang

“…A new resampling method that provides a lower error than four other common interpolation methods under such conditions is introduced.…”
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A K‐band eight‐element reconfigurable phased‐array receiver with high Tx‐band rejection by Zhuoheng Xie, Shi Chao Jin, Jia Xing Sun, Dunge Liu, Bo Huang, Yuqian Yang, Chenyu Mei, Jinhuai Su, Jun Huang, Xiulong Wu, Lei Zhang

“…Meanwhile, the measured root mean square (RMS) gain error and RMS phase error are confined within 0.8 dB and 3.7°, respectively.…”
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