Physiology-informed regularisation enables training of universal differential equation systems for biological applications. by Max de Rooij, Balázs Erdős, Natal A W van Riel, Shauna D O'Donovan

“…On the other hand, data-driven approaches such as machine learning models require large volumes of data to produce generalisable models. …”
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Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering. by Guanqun Wang

“…Furthermore, four widely recognized machine learning methods are employed to classify the clustering results, achieving over 95% classification accuracy on the test set. …”
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Experimental and Analytical Studies on Improved Feedforward ML Estimation Based on LS-SVR by Xueqian Liu, Hongyi Yu

“…Maximum likelihood (ML) algorithm is the most common and effective parameter estimation method. However, when dealing with small sample and low signal-to-noise ratio (SNR), threshold effects are resulted and estimation performance degrades greatly. …”
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Extreme Learning-Based Robust Adaptive Path Tracking Control of Underactuated Unmanned Surface Vessel by Xinyu HE, Ning WANG, Haojun WU

“…An extreme learning-based robust adaptive path tracking control scheme was proposed for underactuated unmanned surface vessels(USVs) with unknown dynamics, parameter uncertainties, and disturbances. Firstly, the surge-guided line-of-sight guidance law was used to guide the surge speed and heading angle at the same time, so as to avoid the singularity of the guidance process and make the USV converge to the desired path quickly. …”
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Advanced bearing fault detection at varying rotational speeds using PSO-optimized SVM and CDET feature selection by Hongxu Chai, Xiaoshi Ma, Feng Zhu, Yandong Hu

“…Furthermore, the parameters of both CDET and support vector machine (SVM) classifiers are jointly optimized by PSO, resulting in enhanced classification accuracy and computational efficiency. …”
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Intra-Net Cognitive Radio Intelligent Utility Maximization using Adaptive PSO-Gradient Algorithm by Imran Ullah Khan

“…Re-configurability and perception are the key features of cognitive radio while latest machine learning techniques like deep learning is used for system adaptation. …”
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Research on an Intelligent Sedimentary Microfacies Recognition Method Based on Convolutional Neural Networks Within the Sequence Stratigraphy of Well Logging Curve Image Groups by Xinyi Yuan, Xidong Wang, Shutian Wang, Feng Tian, Zichun Yang

“…Traditional facies interpretation methods, reliant on manual log-response parameter analysis, are constrained by interpreter subjectivity, reservoir heterogeneity, and inefficiencies in resolving thin interbedded sequences and concealed fluvial sand bodies—issues marked by high interpretive ambiguity, prolonged cycles, and elevated costs. …”
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Structural health monitoring of turbo generator foundation by Fatemeh Sharafi, Reza Karami Mohammadi

“…Analytical mode decomposition (AMD) and experimental mode decomposition (EMD) methods are both used for modal parameter identification. A genetic algorithm is further used for finite element model updating and damage detection. …”
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Fast binary logistic regression by Nurdan Ayse Saran, Fatih Nar

“…This study presents a novel numerical approach that improves the training efficiency of binary logistic regression, a popular statistical model in the machine learning community. Our method achieves training times an order of magnitude faster than traditional logistic regression by employing a novel Soft-Plus approximation, which enables reformulation of logistic regression parameter estimation into matrix-vector form. …”
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Cascadia Daily GNSS Time Series Denoising: Graph Neural Network and Stack Filtering by Loïc Bachelot, Amanda Thomas, Diego Melgar, Jake Searcy, Yu-Sheng Sun

“…We compared the GNN approach with three simple stack filtering methods, which performed comparably in many situations but are more sensitive to parameter choices. For all methods, substantial noise reduction removes artifacts that could impact geophysical interpretations. …”
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Pure pursuit method use to control unmanned motor grader by R. Yu. Sukharev

“…Some theoretical studies of the mathematical model have been carried out and the dependencies of the integral criterion on the design and operational parameters of the grader, as well as on the parameter of the control method (visibility range) have been obtained. …”
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Internet of things driven hybrid neuro-fuzzy deep learning building energy management system for cost and schedule optimization by Deepshikha Shrivastava, Deepshikha Shrivastava, Prerna Goswami

“…For two years from December 2021 to December 2023 the energy consumption and twenty seven associated energy parameters was monitored by developing an IoT enabled BEMS. …”
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A Novel Shearer Cutting State Recognition Method Based on Improved Variational Mode Decomposition and LSSVM with Acoustic Signals by Zhongbin Wang, Bin Liang, Lei Si, Kuangwei Tong, Chao Tan

“…On this basis, an improved gravitational search algorithm (IGSA) is designed by using the position update mechanism of Levy flight strategy to find the optimal parameter combination of VMD. Then, the feature extraction is achieved by calculating the envelope entropy and kurtosis of the decomposed intrinsic mode functions (IMFs). …”
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Substrate-aware computational design of two-dimensional materials by Arslan Mazitov, Ivan Kruglov, Alexey V. Yanilkin, Aleksey V. Arsenin, Valentyn S. Volkov, Dmitry G. Kvashnin, Artem R. Oganov, Kostya S. Novoselov

“…Finally, we use the ab initio thermodynamics approach to predict the synthesis conditions of the discovered structures in the parameter space of the commonly used chemical vapor deposition technique.…”
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A New Hyperspectral Image Identification Method Based on LSDA and OSELM by Chengjiang Zhou, Mingli Yang, Sasa Duan, Lu Shao, Zhilin Zhang, Yunfei Liu

“…In the future, its computational complexity and parameter robustness are expected to be further improved and applied in practical application scenarios.…”
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Estimation of Gestational Age by Using Fetal Kidney Length in Comparison with Other Biometric Indices by Sushmitha Alias Tulasi, R Sarvesh, T Shriram

“…Conclusion: FKL is a reliable parameter for gestational age estimation, particularly in the third trimester. …”
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An Improved YOLOv7-Tiny-Based Algorithm for Wafer Surface Defect Detection by Mengyun Li, Xueying Wang, Hongtao Zhang, Xiaofeng Hu

“…To address the shortcomings of manual inspection and the limitations of existing machine learning methods, this paper proposes a wafer defect detection algorithm based on an improved YOLOv7-tiny. …”
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Driving range estimation for electric bus based on atomic orbital search and back propagation neural network by Hanchen Ke, Jun Bi, Yongxing Wang, Yu Zhang

“…To solve this problem, an accurate estimation method for the driving range of electric buses based on atomic orbital search (AOS) algorithm and back propagation neural network (BPNN) was used, in which a long‐term bus operation dataset under different driving conditions is utilized to train BPNN, and then weight and bias are taken as the first generation provided for AOS approach to find a more appropriate parameter combination. Simulation and experimental analysis show that the algorithm introduced in this paper has higher prediction accuracy and efficiency compared to the traditional machine learning algorithms, that compared with BPNN, AOSBP reduced MAE, RMSE and MAPE by 85.6%, 50.9% and 64.6%, respectively, which effectively relieves range anxiety, and ensures the normal operation of the electric bus fleet.…”
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Bank Customer Segmentation and Marketing Strategies Based on Improved DBSCAN Algorithm by Xiaohua Yan, Yufeng Li, Fuquan Nie, Rui Li

“…Using machine learning techniques, the study explores the relationship between customer attribute features and fixed deposits. …”
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A study on the causes of the inconsistencies of the microstructure of welded joints of steel wire cord by I. V. Borisovets, T. P. Kurenkova, A. A. Sakharnaya

“…Relevance: the increase in the number of destruction of welded joints of the metal wire cord due to discrepancies in the microstructure of the welded seam.Purpose: to find the roots of defects in welded joints of metal wire cord to reduce the number of inconsistencies in this parameter and study the features of the formation of the microstructure of welded joints.Methods of research: as a material for research the metal wire cord of various designs made in steel – wire shop No. 2 of OJSC «BSW – Management Company of Holding «BMC» – a rod of own production was applied; the study was conducted using a Nikon SMZ 1000 stereoscopic microscope with a video system and an inverted metallographic microscope OLIMPUS GX-51 with a video system; measurement of hardness was carried out according to Vickers with a load of 0.5 kg on a hardness testing ZWICK 3Х5624АТ.Research results: the regularities and causes of the formation of mismatch of the microstructure of welded joints during welding on metal: incorrect setting of the welding machine (slowing down of the welding carriage); mismatch of the tempering temperature (a faulty button or operation home run twice); a small dwell time in the terminals (jaws) for tempering; inadequate execution of Regulation of the welded connection of the operator’s actions (pass or failure of the operation «tempering of the weld»); influence of external environmental factors (microclimate) of the operator’s workplace.…”
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