Measurement Error Estimation Method of Field Service Electricity Energy Meters under the Condition of Big Data by DAI Yan-jie, DONG Xian-guang, LIU Ya-qi, LIANG Ya-jie, LIU Xiao, QI Jia, SUN Yong-quan

“…In order to better explore the measurement performance of field service electricity energy meters under multi-dimensional influence conditions, and infer measurement error under standard laboratory conditions, a measurement error estimation method of field service electricity energy meters is proposed based on big data analysis technology, which realizes on-line measurement error estimation by combining environmental data and electric factor data of field operation. …”
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Stochastic parameter-optimized car-following model considering heterogeneous traffic flow by PAN Yiyong, QUAN Yongjun, GUAN Xingyu

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Accurate prediction of college students' information anxiety based on optimized random forest and category boosting fusion model by Bin Wang, Li Shao

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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

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A novel Parrot Optimizer for robust and scalable PEMFC parameter optimization by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Gulothungan G., Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…The objective function Sum of Squared Error (SSE) for stack voltage is minimized using different algorithms for comparative analysis. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

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Back-Analysis of Parameters of Jointed Surrounding Rock of Metro Station Based on Random Forest Algorithm Optimized by Cuckoo Search Algorithm by Xinping Guo, Annan Jiang, Xiang Liu

“…The parameter determination is transformed into a global optimization problem. In this method, the mean square error between the measured displacement (stress) and the calculated displacement (stress) is taken as the objective function, and the joint parameters are taken as the decision variables. …”
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Seven-parameter PEMFC model optimization using an battlefield optimization algorithm by Manish Kumar Singla, S.A. Muhammed Ali, Jyoti Gupta, Pradeep Jangir, Arpita, Ramesh Kumar, Reena Jangid, Mohammad Khishe

“…Using Sum Squared Error (SSE) to minimize the difference between estimated and actual cell voltages, BfOA outperformed other optimization algorithms in determining parameters for six PEMFC models under varying operating conditions. …”
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Estimation of heat transfer parameters by using trained POD-RBF and Grey Wolf Optimizer by Minh Ngoc Nguyen, Nha Thanh Nguyen, Thien Tich Truong

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Predictive Modeling and Optimization of Hot Forging Parameters for AISI 1045 Ball Joints Using Taguchi Methodology and Finite Element Analysis by Naiyanut Jantepa, Nattarawee Siripath, Surasak Suranuntchai

“…To address these challenges, this research employed the Taguchi method in conjunction with a finite element (FE) simulation to identify the optimal forging parameters. The Arrhenius constitutive model, based on the Zener–Hollomon parameter, was applied to predict the flow stress with a high level of accuracy, achieving a coefficient of determination (R²) of 0.968 and an average absolute relative error (AARE) of 7.079%. …”
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Multiobjective Time-Space Grid Optimization of Lithium-Ion Electrochemical Model Based on Stability Analysis and Limit Region Decoupling Strategy by Libin Zhang, Minghang Zhang, Hongying Shan, Guan Xu, Jingsheng Dong, Xuemeng Bai

“…The SPMe model achieved a voltage estimation root mean square error (RMSE) of less than 5 mV, while maintaining a simulation time of less than 10 ms per second. …”
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Comparative Analysis of RF, SVR with Gaussian Kernel and LSTM for Predicting Loan Defaults by Konstantinos Kofidis, Cătălina Lucia Cocianu

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Noise Reduction of Steam Trap Based on SSA-VMD Improved Wavelet Threshold Function by Shuxun Li, Qian Zhao, Jinwei Liu, Xuedong Zhang, Jianjun Hou

“…Compared to traditional thresholding methods, this approach increases the signal-to-noise ratio and reduces the root-mean-square error, significantly enhancing the noise reduction effect on the steam trap’s background noise signal.…”
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Optimized Machine Learning-Augmented Hybrid Empirical Models for AlGaN/GaN HEMTs: A Comprehensive Analysis by Ahmad Khusro, Saddam Husain, Mohammad Hashmi

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Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency by X. Little Flower, S. Poonguzhali

“…Abstract A novel hybrid approach combining neighborhood component analysis (NCA) and metaheuristic optimization algorithms is proposed to improve the classification accuracy of electromyography (EMG) signals while reducing the feature set size and computational time. …”
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Modeling Analysis and Simulation Verification for Drive Tooth Stress of Rubber Track Wheel by Zihan Zhao, Xihui Mu, Fengpo Du, Jianhua Guo

“…The simulation results show that the maximum error between the simulation data and the calculation data is about 11.76%，so the mathematical model can be applied to the analysis of the driving tooth stress. …”
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An integrated approach to image quality: comparative analysis of bilinear and nearest neighbor interpolation by Wusat Ullah, Seher Ilyas, Hamza Naveed, Saalam Ali

“…To achieve a thorough evaluation of each interpolation method, we utilize a set of essential quality assessment metrics: Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Grayscale Analysis, and Mean Squared Error (MSE). These metrics were selected to provide a balanced assessment of image sharpness, structural accuracy, and overall visual quality. …”
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Neural Networks for Solving PDEs on Edge Computing Platforms: A Comprehensive Analysis by Segundo Francisco Segura Altamirano, Diana M. Castro Cardenas

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Virtual Machining of Total Knee Replacement Products Based on Finite Element Analysis (FEA) and Re-Design Optimization by ISO 14243 by Setyoadi Yuris, Ismail Rifky, Bayuseno AP., Jujur I Nyoman, Novriansyah Robin, Darmanto, Prawibowo Hartanto, Anggoro P. W.

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Compressive performance of 3D-printed lightweight structures: Infill pattern optimization via Multiple-Criteria Decision Analysis method by Cristina Vălean, Emanoil Linul, Dipen Kumar Rajak

“…The present work addresses a comprehensive compression characterization of Polylactic Acid (PLA) parts produced through the material extrusion (MEX) process, focusing on large strain ranges (0–80 %). Additionally, an optimization study of the infill pattern (IP) was conducted using the Multiple-Criteria Decision Analysis (MCDA) method. …”
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