Rapid screening and optimization of CO2 enhanced oil recovery operations in unconventional reservoirs: A case study by Shuqin Wen, Bing Wei, Junyu You, Yujiao He, Qihang Ye, Jun Lu

“…Based on the results of model interpretability, the genetic algorithm (GA) was coupled with RF (RF-GA model) to optimize the CO2-EOR process. The proposed framework was validated by comparing the GA-RF predictions with simulation results under different reservoir conditions, which yielded a minimum relative error of 0.34% and an average relative error of 5.3%. …”
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Analysis of effectiveness of the program of joined air traffic controlles and pilotes training by A. I. Stepnova, S. M. Stepanov, V. V. Borsoeva, V. A. Borsoev

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Investigation and Optimization of Discharging Performance Enhancement of Phase Change Cold Storage Panel using Embedded Heat Pipes by Tian Shen, Ma Cuiling, Chen Yuhong, Guo Liyuan, Shao Shuangquan, Zhu Tingting, Sun Zhili

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Modeling of Global and Individual Kinetic Parameters in Wheat Straw Torrefaction: Particle Swarm Optimization and Its Impact on Elemental Composition Prediction by Ismael Urbina-Salas, David Granados-Lieberman, Martín Valtierra-Rodríguez, Claudia Adriana Ramírez-Valdespino, David Aarón Rodríguez-Alejandro

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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…This study proposes a method that combines metallurgical mechanism analysis, data analysis, and machine learning to develop a temperature prediction model for VD furnace refining. …”
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Improving the Analytical Method of Convergence Using Runge-Kutta Optimization Algorithm for Solving Fractional-Order Nonlinear Differential Equations by Shwan Abdal, Kais Ibraheem

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Effect of bit-size reduced half-precision floating-point format on image pixel characterization for AI applications by J. Jean Jenifer Nesam, S. Sankar Ganesh, Sitharthan Ramachandran

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Market Efficiency and Stability Under Short Sales Constraints: Evidence from a Natural Experiment with High-Frequency Resolution by Lin-Kun Chan, Chin-Yang Lin, Jin-Huei Yeh

“…Firstly, we derive the theoretical price with put–call parity from seven series index options. Using a “threshold error correction model” (TECM), we find a more efficient price adjustment to new equilibria for upward adjustments than for downward adjustments. …”
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Optimal payload lengths of reliable multicast schemes by ZHU Feng1, WU Ling-shuang2, GU Yuan-tao1

“…Using total transmission time-the time needed to guarantee reliable data dissemination——as judgment criterion,the payload length selection problem was investigated for three multicast solutions which are based on simple feedback retransmission,Reed-Solomon codes,and LT fountain codes,respectively,with the consideration of packet overhead.A theoretical analysis method was proposed to determine the optimal payload lengths,which was verified by simulations.Analyses and simulations indicate,for variable packet overhead sizes and link bit error rates,each method considered has its optimal payload length.As link bit error rate increases,the performance gain brought by the selection of optimal pay-load lengths becomes more significant.Among the three solutions,the reliable multicast solution based on LT fountain codes has the most outstanding performance.…”
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Optimal payload lengths of reliable multicast schemes by ZHU Feng1, WU Ling-shuang2, GU Yuan-tao1

“…Using total transmission time-the time needed to guarantee reliable data dissemination——as judgment criterion,the payload length selection problem was investigated for three multicast solutions which are based on simple feedback retransmission,Reed-Solomon codes,and LT fountain codes,respectively,with the consideration of packet overhead.A theoretical analysis method was proposed to determine the optimal payload lengths,which was verified by simulations.Analyses and simulations indicate,for variable packet overhead sizes and link bit error rates,each method considered has its optimal payload length.As link bit error rate increases,the performance gain brought by the selection of optimal pay-load lengths becomes more significant.Among the three solutions,the reliable multicast solution based on LT fountain codes has the most outstanding performance.…”
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Optimal Subsampling for Upper Expectation Parametric Regression by Zhaolei Liu

“…In classic regression analysis, the error term of the model typically conforms to the requirement of being independent and identically distributed. …”
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Design and Parameter Optimization of a Reciprocating In-Soil Cutting Device in a Green Leafy Vegetable Orderly Harvester by Yue Jin, Jinwu Wang, Zhiyu Song, Renlong Zhang

“…On this basis, the fitted regression equations of the repeated-cutting rate and the miss-cutting rate are established, the miss-cutting rate and the repeated-cutting rate under the optimal parameters are 1.519% and 28.503%, and the corresponding errors with the simulation values are obtained as 11.36% and −0.45%, respectively, which verified the validity of the fitted regression equations. …”
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Analytic Evaluation of the Statistical Power of Accelerated Reliability Demonstration Tests by Philipp Mell, Martin Dazer

“…Comparing test plans by their estimation variance has several disadvantages, as it only considers the type I error. To overcome these disadvantages, the probability of successfully demonstrating a lifetime target is used to implement a statistical power analysis for test plans from a practical perspective. …”
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Ability of clock drawing errors on Mini-Cog test to predict development of delirium after major urological cancer surgery by Shugo Yajima, Yasukazu Nakanishi, Shunya Matsumoto, Naoya Okubo, Kenji Tanabe, Madoka Kataoka, Hitoshi Masuda

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Friction stir welding tool trajectory error on the load capacity of EN AW-2024-T3 aluminum alloy joints by Magdalena Bucior, Rafał Kluz, Andrzej Kubit, Hamed Aghajani Derazkola, Enrico Cestino, Ján Slota

“…Since the FSW-capable robot has low stiffness, a HAAS TM1P milling machine was used to simulate the robot's motion, incorporating recorded deviation errors. The welding process of 1 mm thick sheets was first conducted under ideal rectilinear conditions, establishing optimal parameters: feed rate of 200 mm/min, tool rotational speed of 1517 rpm, and plunge depth of 1.46 mm. …”
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Virtual Validation and Uncertainty Quantification of an Adaptive Model Predictive Controller-Based Motion Planner for Autonomous Driving Systems by Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Satyesh Shanker Awasthi, Michael Khayyat, Stefano Arrigoni, Francesco Braghin

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Wind energy system fault classification and detection using deep convolutional neural network and particle swarm optimization‐extreme gradient boosting by Chun‐Yao Lee, Edu Daryl C. Maceren

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Comparative analysis of lumped and semi-distributed hydrological models for an upland watershed in Ethiopia by Gebiaw T. Ayele, Bofu Yu

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Estimation and diagnostic for single-index partially functional linear regression model with $ p $-order autoregressive skew-normal errors by Lijie Zhou, Liucang Wu, Bin Yang

“…The algorithm uniquely addressed the unit-norm constraint of single-index vectors through reparameterization, thereby overcoming the limitations of conventional EM in nonlinear optimization. Comprehensive simulations demonstrated EM-CALS's superiority over the two-step iterative least squares (TSILS) algorithm, achieving reductions of 1.19% in root mean square error (RMSE), 2.45% in mean square error (MSE), 38.00% in root average squared errors ($ \text{RASE}_{1} $), and 51.35% in $ \text{RASE}_{2} $, respectively, demonstrating a clear advantage in enhancing prediction accuracy. …”
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Research on anti-error operation warning of power grid dispatching based on deep bidirectional gated recurrent neural network by Jinglong He, Dunlin Zhu, Sheng Yang, Jinming Liu, Tianyun Luo, Yuan Fu

“… To improve the security and overall efficiency of grid scheduling work and accurately optimize scheduling decisions, a grid scheduling error-proof operation warning method based on a deep bidirectional gated recurrent neural network is proposed. …”
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