Optimization Design of Diaphragm Profile based on Kriging Model by Geng Hu, Zhigang Chen, Ding Zhang

“…Finally，the initial Kriging model is updated with MP （minimizing the predicted objective function） infill-sampling criterion and genetic algorithm，and the optimal design is obtained via the final Kriging model. …”
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Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

“…The results confirm that the method significantly reduces the bit error rate by 3.3% and improves the success rate of deframing in most experimental wells. …”
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OPTIMIZATION OF HEMISPHERICAL RESONATOR GYROSCOPE STANDING WAVE PARAMETERS by O. S. Khalyutina

“…In this case, if the output signal of the compensating effects should coincide with the ideal signal at the most.…”
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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…This study introduces a novel method to optimize Post-Training Quantization (PTQ), a widely used technique for reducing model size, by integrating Vector Quantization (VQ) with incremental clustering. …”
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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…The downer of a GLSCFB bioreactor provided experimental data on TKN, NH4-N, NO3-N, and TCOD removal. The hybrid optimal intelligence algorithm (BOA-SVR) has improved model accuracy across multiple domains by combining BOA and SVR. …”
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An efficient hybrid Hopfield convolutional neural network for detecting spam bots in Twitter platform by A.V. Santhosh Kumar, N. Suresh Kumar, R. Kanniga Devi

“…This method helps to reduce the feature dimensionality and overfitting issues. In order to improve the optimization algorithm’s searching ability, an X-shaped transfer function is used. …”
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Research on Sparse Code Multiple Access Detection Technology in Satellite Communication Systems by Yiting JIANG, Lidong ZHU

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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

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Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

“…To address the low fitting accuracy of traditional identification methods, a Whale Optimization Algorithm (WOA)-based Gated Recurrent Unit (GRU) system identification model (WOA-GRU) was proposed. …”
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A thermodynamic inspired AI based search algorithm for solving ordinary differential equations by V. Murugesh, M. Priyadharshini, T. R. Mahesh, Esmael Adem Esleman

“…In return, metaheuristic algorithms have become promising alternatives that strongly transform the solution process into an optimization task. …”
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PM2.5 Concentration Prediction Based on Markov Blanke Feature Selection and Hybrid Kernel Support Vector Regression Optimized by Particle Swarm Optimization by Lian-Hua Zhang, Ze-Hong Deng, Wen-Bo Wang

“…Abstract This study employed air quality and meteorological data as research materials and extracted the optimal feature subset by using the approximate Markov blanket-based normal maximum relevance minimum redundancy (nMRMR) algorithm to serve as the input data of the prediction model. …”
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Development of Spectral Clustering Algorithm in Cognitive Diagnosis Model: Approach for Student’s Psychological Growth by Xiao Chang

“…The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…Additionally, a neural network-based forecasting algorithm utilizing the Daubechies wavelet transform is introduced to improve the predictive accuracy of subsurface characteristics. …”
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A comprehensive review of fiber-reinforced topology optimization for advanced polymer composites produced by automated manufacturing by Bence Szederkenyi, Norbert Krisztian Kovacs, Tibor Czigany

“…Accordingly, the review introduces the main TO techniques and the common reinforcement path design strategies using concurrent and sequential optimization approaches. Furthermore, this paper examines the potential transformation of the conventional role of TO algorithms in structural optimization by integrating Artificial Intelligence (AI) into the optimization process [1]. …”
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Finite-Time Control for Satellite Formation Reconfiguration and Maintenance in LEO: A Nonlinear Lyapunov-Based SDDRE Approach by Majid Bakhtiari, Amirhossein Panahyazdan, Ehsan Abbasali

“…This optimization process minimizes energy usage through a hybrid genetic algorithm and simulated annealing (HGASA), resulting in improved performance. …”
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Design and Experiment of a Greenhouse Autonomous Following Robot Based on LQR–Pure Pursuit by Yibin Hu, Jieyu Xian, Maohua Xiao, Qianzhe Cheng, Tai Chen, Yejun Zhu, Guosheng Geng

“…These findings confirm that the designed robot can sustain its payload under most operating scenarios and that the proposed tracking strategy effectively suppresses deviations and improves path-following accuracy.…”
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An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

“…This study addresses the challenge of generating accurate and compact oblique decision trees using self-adaptive differential evolution algorithms. Although traditional decision tree induction methods create explainable models, they often fail to achieve optimal classification accuracy. …”
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Algorithms for Load Balancing in Next-Generation Mobile Networks: A Systematic Literature Review by Juan Ochoa-Aldeán, Carlos Silva-Cárdenas, Renato Torres, Jorge Ivan Gonzalez, Sergio Fortes

“…The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. …”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

“…FAMPA allows for flexibly adjusting population location changes to optimize the balance between global exploration and local exploitation, thus significantly improving both convergence rates and optimization accuracy. …”
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