Model order reduction of boiler system using nature-inspired metaheuristic optimization of PID controller by Anurag Singh, Shekhar Yadav, Nitesh Tiwari, Dinesh Kumar Nishad, Saifullah Khalid

“…Experimental results demonstrate that the PSO-optimized PID controller achieves a 20% reduction in settling time and a 14.68% improvement in Integral Square Error (ISE) compared to conventional tuning methods. …”
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Thermoplastic Labyrinth Seals Under Rub Impact: Deformation Leakage Mechanisms and High Efficiency Optimization by Fei Ma, Zhengze Yang, Yue Liu, Shuangfu Suo, Peng Su

“…A custom designed rub-impact test rig was constructed to measure dynamic forces and validate finite element analysis (FEA) models with an error of 5.1% in predicting tooth height under mild interference (0.25 mm). …”
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Optimizing Precipitation Forecasting and Agricultural Water Resource Allocation Using the Gaussian-Stacked-LSTM Model by Maofa Wang, Bingcheng Yan, Yibo Zhang, Lu Zhang, Pengcheng Wang, Jingjing Huang, Weifeng Shan, Haijun Liu, Chengcheng Wang, Yimin Wen

“…Key predictors identified through variable attribution analysis include temperature, dew point, prior precipitation, and air pressure. …”
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Optimizing Lightweight Recurrent Networks for Solar Forecasting in TinyML: Modified Metaheuristics and Legal Implications by Gradimirka Popovic , Zaklina Spalevic , Luka Jovanovic , Miodrag Zivkovic , Lazar Stosic , Nebojsa Bacanin 

“…Simulations, along with a rigid comparative analysis with other contemporary metaheuristics, are also conducted on a real-world dataset, with the best models achieving a mean squared error (MSE) of just 0.000935 volts and 0.007011 volts on the two datasets, suggesting viability for real-world usage. …”
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Optimization of dye effluent decolorization by halotolerant Halomonas strain D2 in static culture condition by Ali Partovinia, Maryam Otadi, Amirhossein Alaedini

“…In this survey, optimization and variables’ effectiveness study was performed by the response surface methodology (RSM). …”
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Underwater acoustic channel estimation method based on response generative network by XU Ming, ZHANG Qi

“…On this basis, a time-delay-compensated localized analysis algorithm was proposed for 3D reconstruction of underwater signals to reduce feature errors caused by the dynamic changes of the channels. …”
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Machine learning optimization of environmental factors influencing biomass and nutritional composition in local algal species by Aisha Khan, Saleem Ullah, Rifat Ali, Mahwish Rehman, Said Moshawih, Khang Wen Goh, Long Chiau Ming, Lai Ti Gew

“…A novel metric, W_new, combining performance and error metrics, facilitated robust model evaluation and hyperparameter tuning. …”
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Detection of abnormal tourist behavior in scenic spots based on optimized Gaussian model for background modeling by Liu Xiaohua

“…The study proposed a background model constructed by an optimized Gaussian mixture model based on the background subtraction method to eliminate the background interference. …”
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Scalable FPGA Implementation of a Reliability-Based Direct Turbo Decoder for Short Block Codes by Senthil Murugan, Ramesh Bhakthavatchalu, Karthi Balasubramanian, B. Yamuna, Deepak Mishra, Sree Ranjani Rajendran

“…Additionally, a fixed-point quantization study confirms that a 16-bit representation of reliability values introduces negligible error, offering further scope for area and power optimization. …”
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Ferroelectric Transistor-Based Synaptic Crossbar Arrays: The Impact of Ferroelectric Thickness and Device-Circuit Interactions by Chunguang Wang, Sumeet Kumar Gupta

“…First, based on a physics-based model of multidomain FeFETs calibrated to experiments, we analyze the impact of <inline-formula> <tex-math notation="LaTeX">$T_{\text {FE}}$ </tex-math></inline-formula> on the characteristics of FeFETs as synaptic devices, highlighting the connections between the multidomain physics and the synaptic attributes. Based on this analysis, we investigate the impact of <inline-formula> <tex-math notation="LaTeX">$T_{\text {FE}}$ </tex-math></inline-formula> in conjunction with other design parameters, such as number of bits stored per device (bit slice), wordline (WL) activation schemes, and FeFETs width on the error probability, area, energy, and latency of CiM at the array level. …”
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State of Health Estimation for Lithium-Ion Battery Using Partial Incremental Capacity Curve and Transfer Learning by Sheng Huang, Xuemei Wang, Longyun Kang, Di Xie, Xi Zhang

“…For the base model, the root mean square error is 0.0033. With the transfer learning method, which utilized only 1.6% of the target domain data, the root mean square error is 0.0039. …”
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A framework of crop water productivity estimation from UAV observations: A case study of summer maize by Minghan Cheng, Ni Song, Josep Penuelas, Matthew F. McCabe, Xiyun Jiao, Yuping Lv, Chengming Sun, Xiuliang Jin

“…Key scientific findings demonstrate: (1) SEBAL outperformed FAO-56 in daily ET estimation (R² = 0.76 vs. 0.71, RMSE = 1.15 vs. 1.31 mm/d). (2) The machine learning yield model exhibited robust predictive capability (R² = 0.77, RMSE = 0.98 t/ha), successfully capturing yield variability across treatments. (3) Error propagation analysis validated framework reliability (CWP RMSE = 0.67 kg/m³), effectively differentiating CWP performance among management practices. …”
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A Sea Horse Optimization-Based Approach for PEM Fuel Cell Model Parameter Estimation by Ali Erduman, Gizem Hazar, Evrim Baran Aydın

“…This study aims to determine the model parameters of proton exchange membrane fuel cells (PEMFC) by employing the Sea Horse Optimization (SHO) algorithm, a novel metaheuristic approach inspired by natural behaviors. …”
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Energy optimization and plant comfort management in smart greenhouses using the artificial bee colony algorithm by Muhammad Jawad, Fazli Wahid, Sikandar Ali, Yingliang Ma, Ahmed Alkhyyat, Jawad Khan, Youngmoon Lee

“…The overall efficacy of the fuzzy controllers that switch On/Off the actuators was obtained by minimizing the error between the best estimates of environmental factors and the ABC optimized values. …”
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Comprehensive Evaluation of Operation Safety of Earth-rock Dams Based on Weight Optimization-cloud Model by ZHANG Jianwei, WU Weitao, HOU Ge, HUANG Jinlin, WANG Bingpeng, LIU Hongze, HU Zixu

“…Taking 95% engineering accuracy as the measurement standard, it was found that among these 20 random experiments, three experiments failed to satisfy the condition when the cloud droplet number was 2 000, and all experiments met the requirement when the cloud droplet number was 5 000. Since the error did not change significantly when the number of cloud drops continued to increase, 5 000 was taken as the optimal number of cloud drops to balance computational efficiency and accuracy.Results and DiscussionsThe established evaluation model was applied to the earth and rock dam of the Helong Reservoir in Guangdong Province. …”
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A Note on the Perturbation of arithmetic expressions by Baghdad Science Journal

“…The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. …”
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Development and Validation of a Population Pharmacokinetics Model of Perampanel for Pediatric Epilepsy Patients for Optimized Dosing by Yu L, Mao F, Chen S, Liu J, Xiao J, Chen M, Luo H, Yu Z, Dai H

“…Goodness-of-fit plots and bootstrap analysis were employed to evaluate the final model. …”
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Social Cognitive Optimization Algorithm for Approximate Path Generation Synthesis of Spherical 4R Linkage by Che Linxian, Huang Yonggang, Du Li

“…The model takes the minimizing sum of squares for path errors as the objective function， and the existing crank，length coordination，and transmission angle restriction as the constraints. …”
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A Robust Population Dynamics Model With Carrying Capacity Constraints for Centrally Coordinated Distributed Optimization by German Obando, Andres Pantoja

“…RCCRD further enhances robustness through a self-correcting mechanism, ensuring constraint satisfaction and reliable performance even with computational errors. Theoretical analysis demonstrates the convergence properties of (R)CCRD, and comparative simulations reveal that RCCRD outperforms some existing methods in terms of runtime, optimality gap, and constraint satisfaction, particularly in noisy environments. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…The feature selection process was optimized using Gini importance metrics, with model performance evaluated through mean squared errors and mean absolute errors.…”
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