Design of Periodic Neural Networks for Computational Investigations of Nonlinear Hepatitis C Virus Model Under Boozing by Abdul Mannan, Jamshaid Ul Rahman, Quaid Iqbal, Rubiqa Zulfiqar

“…A comparative analysis with established numerical methods is provided, where performance metrics are illustrated using a range of graphical tools, including box plots, histograms, and loss curves. The absolute error values, ranging approximately from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>6</mn></mrow></msup></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>10</mn></mrow></msup></semantics></math></inline-formula>, demonstrate the precision, convergence, and robustness of the proposed approach, highlighting its potential applicability to other nonlinear epidemiological models.…”
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Predicting motor insurance claim incidence using generalized and tree-based models: A comparative statistical approach by Eslam Abdelhakim Seyam

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A parsimonious model for classifying the traffic state of urban road networks: A two-stage regression approach by Wei Huang, Dalin Tang, Xin Qiao, Guojun Chen

“…Third, the developed model is evaluated with three performance indicators, namely, the mean squared error (MSE), mean absolute error (MAE), and mean relative error (MRE). …”
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Design and implementation of an intelligent sports management system (ISMS) using wireless sensor networks by ZhiGuo Zhu

“…To evaluate the system performance in different scenarios, we performed many experiments, which show that the proposed ISMS model shows the system efficacy in improving accuracy (0.94), specificity (0.97), recall (0.91), precision (0.93), F1 score (0.95), mean absolute error (MAE) (0.6), mean square error (MSE) (0.8), and root mean square error (RMSE) (0.9), compared to traditional methods. …”
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A robust quantification of H2O in silicate glasses through micro-Raman spectroscopy: insights on the compositional effect by Filippo Ridolfi, Diego González-García

“…These equations are reproducible and easily applicable to both experimental and natural glasses. …”
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Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…As the predication period increased, the proposed model achieved a root mean square error (RMSE) of 2.11 m3/s, a mean absolute error (MAE) of 1.32 m3/s, a mean absolute percentage error (MAPE) of 73.76%, and a Nash-Sutcliffe efficiency (NSE) coefficient of 0.94. …”
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Comparison of the collapse frequency and failure probability of buildings by Dirk Proske, Michael Schmid

“…Should this correspond to the facts, the basic safety concept of modern building standards, which generally excludes human error, would only be applicable in these regions to a limited extent. …”
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Nonlinear Regressive Maximum Correntropy Extended Kalman Filter With Student&#x2019;s t-Kernel for GPS Navigation by Amita Biswal, Dah-Jing Jwo

“…Performance evaluations through various error technique demonstrate the effectiveness of the proposed method in improving GPS positioning accuracy, highlighting its broader applicability in real-world systems such as GPS navigation and radar-based measurements.…”
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Prediction of the Residual Compressive Strength of Rice Husk Ash Concrete after Exposure to Elevated Temperatures Using XGBoost Machine Learning Algorithm by Elvis Ang'ang'o, Silvester Abuodha, Siphila Mumenya

“…The model accuracy was checked using statistical scores: coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE). SHAP values were used for feature importance analysis. …”
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A New Automated Way to Measure Polyethylene Wear in THA Using a High Resolution CT Scanner: Method and Analysis by Gerald Q. Maguire Jr., Marilyn E. Noz, Henrik Olivecrona, Michael P. Zeleznik, Lars Weidenhielm

“…This approach is applicable clinically as it utilizes readily available computed tomography imaging systems and requires only five minutes of human interaction.…”
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Efficiency Enhancement and Estimation of Photovoltaic Energy Generation Using Dual-Axis Tracking Systems by Aditya Aggarwal, Himanshu Himanshu, Manav Sidana, Girish Gupta, Ishtdeep Singh Sodhi, Anamika Sharma

“…The relevance of these models is analysed based on multiple types of error such as MAE, MSE, RMSE, and R². …”
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Research on the Tunable Optical Alignment Technology of Lidar Under Complex Working Conditions by Jianfeng Chen, Jie Ji, Chenbo Xie, Yingjian Wang

“…Additionally, the average horizontal wind speed error at 30 km decreases from 11.3 m/s to 4.4 m/s, with a minimum error of approximately 1 m/s. …”
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Quantum Surface Topological Code for Bell State Stabilization in Superconducting Physical Qubit Systems by Jordi Fabián González-Contreras, Erik Zamora, Jesús Yaljá Montiel-Pérez, Juan Humberto Sossa-Azuela, Elsa Rubio-Espino, Víctor Hugo Ponce-Ponce

“…In this study, an experimental advancement in Bell state stabilization is presented, which utilizes surface codes for quantum error correction across three quantum computers: ibm_fez, ibm_torino, and ibm_brisbane. …”
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A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology by Aymen Mudheher Badr, Lamia Chaari Fourati, Samiha Ayed

“…The resulting images were tested against a number of important metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), bit error rate (BER), Signal-to-Noise Ratio (SNR), Normalization Correlation (NC) and Structural Similarity Index (SSIM). …”
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Data-driven prediction of rate of penetration (ROP) in drilling operations using advanced machine learning models by Guoli Huang, Sarah Kanaan Hamzah, Pinank Patel, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Dhirendra Nath Thatoi, Deepak Gupta, S. AbdulAmeer, Mariem Alwan, Zahraa Saad Abdulali, Mahmood Jasem Jawad, Hiba Mushtaq, Mohammad Mahtab Alam, Hojjat Abbasi

“…Among the models tested, the Random Forest algorithm demonstrated outstanding performance, achieving an R2 of 0.955, a Mean Squared Error (MSE) of 0.119, and an Average Absolute Relative Error (AARE%) of 7.683, highlighting its reliability and robustness in predicting ROP. …”
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Weld-CNN: Advancing non-destructive testing with a hybrid deep learning model for weld defect detection by Ngo Thi Hoa, Tang Ha Minh Quan, Quoc Bao Diep

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Quantum machine learning: A comprehensive review of integrating AI with quantum computing for computational advancements by Raghavendra M Devadas, Sowmya T

“…The paper tries to collate the state of the art of QML in theoretical underpinnings, practical applications, and directions into the future.…”
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Effective Analytical Computational Technique for Conformable Time-Fractional Nonlinear Gardner Equation and Cahn-Hilliard Equations of Fourth and Sixth Order Emerging in Dispersive... by Mohammed Al-Smadi, Shrideh Al-Omari, Yeliz Karaca, Shaher Momani

“…Besides, the analysis of the error and convergence of the developed technique are discussed. …”
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Crack identification in plates-type structures using natural frequencies coupled with success-history based adaptive differential evolution algorithm by Brihmat Chahira�, Nasreddine Amoura, Samir Lecheb, Hocine Kebir, Mohamed Abdessamed Ait Chikh, Bassima Tablit

“…The outcomes show high accuracy, as indicated by a relative error of the objective function below 0.8%. Overall, the study demonstrates the effectiveness of using the Shade-FEM approach for identifying and characterizing straight cracks in plate-like structures, offering potential applications in various engineering and structural integrity fields.…”
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Calibration of the ångström-Prescott Equation for Solar Radiation Estimation in Minas Gerais by Lucas Santos do Patrocínio Figueiró, Lucas Fernandes Meira, Lucas da Costa Santos

“…For this, we used the following statistical indicators: linear, angular, determination, and correlation coefficients; mean absolute error; root mean square error; concordance index; and performance index. …”
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