Time-Dependent Fragility Functions and Post-Earthquake Residual Seismic Performance for Existing Steel Frame Columns in Offshore Atmospheric Environment by Xiaohui Zhang, Xuran Zhao, Shansuo Zheng, Qian Yang

“…Using the particle swarm optimization back-propagation neural network (PSO-BPNN) model, nonlinear mapping relationships between the characteristic variables and residual seismic capacity are constructed, thereby proposing a residual seismic performance evaluation model for existing multi-aged steel frame columns in an offshore atmospheric environment. …”
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Transient simulation of multi-product pipeline driven by flow mechanisms and operational data by Jian DU, Haochong LI, Qi LIAO, Kaikai LU, Jianqin ZHENG, Xiao YU

“…First, a Deep Neural Network (DNN) model was constructed to establish mapping relationships among flows, pressures, and time-space coordinates of pipeline operation. …”
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Influence of Geometric Effects on Dynamic Stall in Darrieus-Type Vertical-Axis Wind Turbines for Offshore Renewable Applications by Qiang Zhang, Weipao Miao, Kaicheng Zhao, Chun Li, Linsen Chang, Minnan Yue, Zifei Xu

“…To efficiently analyze geometric sensitivity, a surrogate model based on a radial basis function neural network is constructed, enabling fast aerodynamic predictions. …”
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Spatially explicit predictions using spatial eigenvector maps by Guillaume Guénard, Pierre Legendre

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Coastal carbon at risk: forecasting the impacts of sea-level rise on future land cover by Mojtaba Tahmasebi, Julie Bruck, Michael Volk, Emre Tepe, Abhinav Alakshendra, Afsheen Sadaf, Jack A. Puleo

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Artificial Intelligence and Immersive Technologies in Higher Pedagogical Education by V. A. Starodubtsev, O. R. Neradovskaya

“…The conclusion is made that the creativity of innovative lecturers, which is visible in their open educational environments, is a resource for overcoming the reproductive nature of the functioning of pre-trained neural networks. The authors believe that positive feedback in the joint evolution of artificial intelligence (AI) tools and personal segments of the open educational space will contribute to the transformation of the existing information society into a learning society. …”
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Research on concrete structure damage detection based on piezoelectric sensing technology and morphological fractal method by Hanqing Zhong, Liwei Shuai, Dongmin Deng

“…Third, it innovatively constructs an intelligent structural damage recognition model integrating morphological fractal theory and artificial neural network (ANN), and conducts a systematic comparative analysis with the traditional wavelet packet transform (WPT) method, verifying the effectiveness of the proposed MFD-ANN intelligent recognition model in this paper. …”
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Rapid discovering ground states in Lee-Huang-Yang spin-orbit coupled Bose-Einstein condensates via a coupled-TgNN surrogate model by Xiao-Dong Bai, Tianhong Xu, Jian Li, Yong-Kai Liu, Yujia Zhao, Jincui Zhao

“…In this work, a coupled theory-guided neural network (coupled-TgNN) is constructed to explore the ground states of one-dimensional binary Bose-Einstein condensates with spin-orbit coupling and a Lee-Huang-Yang term. …”
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Quantifying hot topic dynamics in scientific literature: An information-theoretical approach. by Artem Chumachenko

“…Understanding the internal structure of scientific discourse is essential for tracking the evolution of research topics and their conceptual interdependencies. …”
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Research Progress and Technology Outlook of Deep Learning in Seepage Field Prediction During Oil and Gas Field Development by Tong Wu, Qingjie Liu, Yueyue Wang, Ying Xu, Jiale Shi, Yu Yao, Qiang Chen, Jianxun Liang, Shu Tang

“…This paper systematically reviews the development history of seepage field prediction methods and focuses on the typical models and application paths of Deep Learning in this field, including FeedForward Neural networks, Convolutional Neural Networks, temporal networks, Graphical Neural Networks, and Physical Information Neural Networks (PINNs). …”
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A Three-Dimensional Nonlinear Dynamic Numerical Optimization of the Risks of Stope Blasting Based on FOA-GRNN by Chengyu Xie, Jie Cao, Dongping Shi

“…Based on the establishment of the first mining stope and its mining method in this area, biosimulation and generalized neural networks were introduced to solve this problem, the coupling of blasting parameters was analyzed, and the 3D nonlinear dynamic coupling model was constructed for numerical simulation. …”
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AI-Driven Surrogate Model for Room Ventilation by Jaume Luis-Gómez, Francisco Martínez, Alejandro González-Barberá, Javier Mascarós, Guillem Monrós-Andreu, Sergio Chiva, Elisa Borrás, Raúl Martínez-Cuenca

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Power Metal Corrosion Evaluation Method Based on Image Feature Analysis by ZHONG Yao, ＲEN Xiao, WU Gao-lin, WANG Qian, WANG Xu-peng, HAO Jian

“…The results show that the color，statistics， wavelet and fractal characteristic parameters of the corrosion image can fully reflect the evolution law and corrosion state of the metal corrosion morphology，and the corrosion evaluation model constructed by the neural networkalgorithm and the multi-dimensional characteristic parameters can accurately evaluate the metal corrosion degree. …”
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Cultivation Method Analysis for Teachers’ Teaching Ability Driven by Artificial Intelligence Technology by Yanfang Chen, Shasha Xu

“…Strengthening construction for teaching staff is an eternal theme of development and construction for colleges, and it is also the focus of personnel management in colleges. …”
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Identification of 30,000 White Dwarf–Main-sequence Binary Candidates from Gaia DR3 BP/RP (XP) Low-resolution Spectra by Jiadong Li, Yuan-Sen Ting, Hans-Walter Rix, Gregory M. Green, David W. Hogg, Juan-Juan Ren, Johanna Müller-Horn, Rhys Seeburger

“…In this study, we construct a catalog of WD–MS binaries using Gaia DR3’s low-resolution BP/RP (XP) spectra. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…At the same time, this paper has constructed a comprehensive dataset in this field, each column contains 9004 data entries.…”
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Predicting the SYM‐H Index Using the Ring Current Energy Balance Mechanism by Lan Ma, Yong Ji, Chao Shen, Gang Zeng, Peng E, YanYan Yang, Shuo Ti, Nisar Ahmad

“…Therefore, the energy balance mechanism of the ring current can be used to construct an SYM‐H evolution equation for prediction purposes. …”
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A hybrid VMD-LSTM-SVR model for landslide prediction by Nianhong Wang, Meijun Wang, Jun Zhang

“…This study employs the Long Short-Term Memory (LSTM) neural network and Support Vector Regression (SVR), combined with the Variational Mode Decomposition (VMD) algorithm, to construct predictive models. …”
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Real-time prediction of early concrete compressive strength using AI and hydration monitoring by Adam Marchewka, Patryk Ziolkowski, Sebastián García Galán

“…Abstract The continuous evolution of construction technologies, particularly in reinforced concrete production, demands advanced, reliable, and efficient methodologies for real-time monitoring and prediction of concrete compressive strength. …”
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Insights into the dependence of post-stroke motor recovery on the initial corticospinal tract connectivity from a computational model by Dongwon Kim, Leah M. O’Shea, Naveed R. Aghamohammadi

“…The model emulates biologically plausible evolutions of primary motor descending tracts, based on activity-dependent or use-dependent plasticity and the preferential use of more strongly connected neural circuits. …”
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