Machine learning modeling for thermochemical biohydrogen production from biomass by Yingju Chang, Wei Wang, Jo-Shu Chang, Duu-Jong Lee

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Analysis of Offshore Pile–Soil Interaction Using Artificial Neural Network by Peiyuan Lin, Kun Li, Xiangwei Yu, Tong Liu, Xun Yuan, Haoyi Li

“…The constructed ANN model demonstrates a simple structure with satisfactory predictive performance, achieving average error margins below 6% and low to moderate prediction accuracy dispersion (26%~45%). …”
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Highly sensitive split ring resonator-based sensor for quality monitoring of edible oils by Muhammad Amir Khalil, Wong Hin Yong, Tehseen Batool, Ahasanul Hoque, Lo Yew Chiong, Hui Hwang Goh, Tonni Agustiono Kurniawan, Mohamed S. Soliman, Mohammad Tariqul Islam

“…Abstract This research presents the design and analysis of a compact metamaterial (MTM)-based star-shaped split-ring resonator (SRR) enclosed in a square, constructed on a cost-effective substrate for liquid chemical sensing applications. …”
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Prediction of crystalline structure evolution during solidification of aluminum at different cooling rates using a hybrid neural network model by Rafi B. Dastagir, Shorup Chanda, Farsia K. Chowdhury, Shahereen Chowdhury, K. Arafat Rahman

“…The performance of the hybrid model is assessed using mean squared error (MSE), mean absolute error (MAE), and the coefficient of determination (R²). …”
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Autoencoder-Driven Fiducial Landmark Identification in 3D Brain MRI for Neuroimaging Alignment by G. Deepali, H. Anitha, B. P. Swathi, M. V. Suhas

“…This method offers a scalable and efficient solution for clinical and research applications, facilitating more reliable head modeling, source localization, and multimodal image integration.…”
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Optimizing battery health monitoring in electric vehicles using interpretable CART–GX model by Mohnish Karthikeyan B, Anirudh N, Navaneetha Krishnan S, Christopher Columbus C, Aravind C. K

“…The proposed model achieved exceptional performance, with a root mean square error (RMSE) of 0.0130 %, mean absolute error (MAE) of 0.0087 %, and an R² value of 99.999 % on the NASA dataset, and maintained robust accuracy on the CALCE dataset, achieving RMSEs as low as 1.23 % and R² values exceeding 99 %. …”
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Real-time implementation of nonlinear model predictive control for high angle of attack Maneuvers in fighter aircrafts using deep learning by Muhammad Faheem Manzoor, Joel A. Paulson, Yasir Awais Butt, Fazal-ur Rehman, Aamer Iqbal Bhatti

“…Since not all the states of the system are measured, we also combine the deep learning based NMPC approach with an unscented Kalman filter (UKF) as well as show how this scheme can be easily modified to be offset-free (i.e. remove steady-state error due to persistent disturbances and modelling error). …”
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Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications by Asif Mehmood, Afaq Muhammad, Faisal Mehmood, Wang-Cheol Song

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A novel EEG artifact removal algorithm based on an advanced attention mechanism by Rui Jiang, Shen Tong, Jiawei Wu, Haowei Hu, Ran Zhang, Heng Wang, Yan Zhao, Weixin Zhu, Shuyan Li, Xiao Zhang

“…Moreover, RRMSE t (relative root mean square error in the temporal domain) and RRMSE f (relative root mean square error in the frequency domain) decrease by 6.94% and 3.30%.…”
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Remote sensing in the estimation of evapotranspiration of tomato cultivation for industrial processing by Carolina Carvalho Rocha Sena, José Alves Júnior, João Mauricio Fernandes Souza, Adão Wagner Pego Evangelista, Rafael Battisti, Derblai Casaroli, Elson de Jesus Antunes Junior

“…This study evaluated the performance of the SAFER and METRIC algorithms to estimate the actual evapotranspiration (ETa) of irrigated tomato crops for industrial processing in the south-central region of Goiás, Brazil. The research was conducted in eight tomato-producing areas using center-pivot irrigation during the 2018 and 2019 harvests. …”
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Advanced predictive modeling of shear strength in stainless-steel column web panels using explainable AI insights by Sina Sarfarazi, Rabee Shamass, Federico Guarracino, Ida Mascolo, Mariano Modano

“…The Extra Trees Regression algorithm demonstrated the highest predictive performance, achieving R² = 0.987, mean absolute error (MAE) = 3.575 kN, and root mean square error (RMSE) = 6.464 kN for the entire dataset. …”
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Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries by Sadiqa Jafari, Jisoo Kim, Wonil Choi, Yung-Cheol Byun

“…The models were assessed using evaluation metrics such as Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and R-squared <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>. …”
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A Method for Predicting the Main Indicators of Cardiopulmonary Stress Testing for Patients with Chronic Heart Failure by A. S. Krasichkov, E. Mbazumutima, F. Shikama, E. M. Nifontov

“…More research is needed to improve the accuracy of the assessment for using in medical applications aimed to the modernization of methods and equipment for stress testing of the patients.…”
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Published population pharmacokinetic models of mycophenolate sodium: a systematic review and external evaluation in a Chinese sample of renal transplant recipients by Tong Gao, Wen Xu, Xiao Li, Qie Guo, Donghua Liu, Xiaolei Zhang, Ping Leng, Jialin Sun

“…To advance individualized medication for MPS based on popPK, future research must prioritize the investigation of potential covariates. …”
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AI-Powered Forecasting of Environmental Impacts and Construction Costs to Enhance Project Management in Highway Projects by Joon-Soo Kim

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An Investigation of Interpolation Techniques to Generate 2D Intensity Image From LIDAR Data by Imran Ashraf, Soojung Hur, Yongwan Park

“…Light detection and ranging (LIDAR) has become a part and parcel of ongoing research in autonomous vehicles. LIDAR efficiently captures data during day and night alike; yet, data accuracy is affected in altered weather conditions. …”
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Resultados del examen estatal del perfil Atención Estomatológica de la Licenciatura en Tecnología de la Salud by Dunia Mulet Sarmiento, Yoandra Ramírez Arias, Elizabeth González Arévalo, Orlin González Sánchez

“…El tema con mayor índice de error en su tratamiento fue la promoción de salud.  …”
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Spatiotemporal Distribution of Soil Thermal Conductivity in Chinese Loess Plateau by Yan Xu, Yibo Zhang, Wanghai Tao, Mingjiang Deng

“…The results show that the LT model is the best in the relevant evaluation indices, with a determination coefficient (<i>R</i>²) of 0.84, root mean square error (<i>RMSE</i>) of 0.18, and relative error (<i>RE</i>) of 0.16. …”
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Filling-well: An effective technique to handle incomplete well-log data for lithology classification using machine learning algorithms by Sherly Ardhya Garini, Ary Mazharuddin Shiddiqi, Widya Utama, Alif Nurdien Fitrah Insani

“…Results indicated that XGBoost was the most efficient and accurate, especially for RHOB, NPHI, DTCO, and DTSM, with the lowest Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. …”
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Enhancing Time Series Product Demand Forecasting With Hybrid Attention-Based Deep Learning Models by Xuguang Zhang, Pan Li, Xu Han, Yongbin Yang, Yiwen Cui

“…Experimental results show that the HA-LSTM outperforms state-of-the-art baselines, including ARIMA, Prophet, and vanilla LSTM models, achieving a 15% improvement in Mean Absolute Percentage Error (MAPE) and a 12% reduction in Root Mean Square Error (RMSE). …”
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