Research on prediction method of well logging reservoir parameters based on Multi-TransFKAN model by Huazhong Yang, Zhang Chong, Lei Xiong, Wenhao Xiong, Guilan Lin, Kaiwen Huang, Wenyi Zhang

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TECTONOPHYSICAL INTERPRETATION OF EARTHQUAKE FOCAL MECHANISMS OF THE ZAGROS SYSTEM by O. B. Gintov, E. Ya. Kolesnikova, A. V. Murovskaya, Y. M. Volfman

“…This means that seismogenic zones are distinguished; structural and kinematic characteristics of such zones are determined by parameters of stereographic models of corresponding types of seismogenesis (Figures 4 and 5). …”
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Minimal metabolic pathway structure is consistent with associated biomolecular interactions by Aarash Bordbar, Harish Nagarajan, Nathan E Lewis, Haythem Latif, Ali Ebrahim, Stephen Federowicz, Jan Schellenberger, Bernhard O Palsson

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Analysis of knee fold structure model in Nanchuan Block of southeastern Chongqing by NI Feng,ZHU Feng,MENG Qingli

“…Previously, the structural interpretation of the Nanchuan block primarily identified faulted anticlines constrained by major reverse faults, without adequately addressing the structural deformation across the entire belt. …”
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Zipf's Law, Hierarchical Structure, and Cards-Shuffling Model for Urban Development by Yanguang Chen

“…A card-shuffling model is built to interpret the relation between Zipf's law and hierarchy of cities. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…Computational linguistics is deeply embedded in algorithmic financial models and reshapes cost forecasting frameworks through data-driven semantic interpretation. …”
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Orthogonal splitting of the Riemann curvature tensor and its implications in modeling compact stellar structures by A. Rehman, Tayyab Naseer, Nazek Alessa, Abdel-Haleem Abdel-Aty

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Machine learning models for clinical and structural knee osteoarthritis prediction: Recent advancements and future directions by Gabby B. Joseph, Charles E. McCulloch, Michael C. Nevitt, Nancy E. Lane, Sharmila Majumdar, Thomas M. Link

“…This review highlights recent advances in ML model development across four OA outcome domains: clinical, structural (radiographic and MRI-based), and surgical endpoints, each addressing different but interrelated aspects of the disease.For clinical outcomes, ML studies have focused on predicting changes in patient-reported clinical measures (e.g., pain and function). …”
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TBM construction risk analysis based on fuzzy Bayesian network by Fangdi Xie, Yong Zhou

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Methodology for acid treatment design considering structural features of the bottomhole area by A. G. Malov, L. S. Kuleshova, R. A. Gilyazetdinov, R. F. Yakupov

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Contextualizing Innovation Investor Behaviour Through Structural Simulation Modelling of Influential Factors

“…This study aims to examine the interconnections between self-efficacy, self-determination, and intrinsic motivation among individual investors; to delineate the relationships between intrinsic and extrinsic motivation, investor attitudes, perceived risk, and loyalty; and to develop a conceptual model that synthesizes these relationships. The research methodology is based on interpretive structural modelling (ISM), ensuring a systematic exploration of factor interdependencies. …”
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5G Networks Security Mitigation Model: An ANN-ISM Hybrid Approach by Rafiq Ahmad Khan, Habib Ullah Khan, Hathal Salamah Alwageed, Hussein Al Hashimi, Ismail Keshta

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A Novel Hyper-Heuristic Algorithm with Soft and Hard Constraints for Causal Discovery Using a Linear Structural Equation Model by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…Acyclic directed graphs (DAGs) are the most commonly used tool in causal modeling because of their excellent interpretability and structural properties. …”
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PARAMETERS AFFECTING THE STRUCTURAL ANALYSIS OF A TUNNEL STRUCTURE EXPOSED TO FIRE by Omid Pouran, Reinhard Harte, Carsten Peter

“…The critical corresponding stresses and material behaviour are compared and interpreted at different time stages. The main parameters affecting the accuracy and convergence of the results of structural analysis for the used model are identified: defining a realistic fire action, using concrete material model fulfilling the requirements of fire situation in tunnels, defining appropriate time intervals for load implementations. …”
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ToxBERT: an explainable AI framework for enhancing prediction of adverse drug reactions and structural insights by Yujie He, Xiang Lv, Wulin Long, Shengqiu Zhai, Menglong Li, Zhining Wen

“…Additionally, many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints, which can introduce bias. …”
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Single-Mode and Dual-Mode Nongomogeneous Dissipative Structures in the Nonlocal Model of Erosion by A. M. Kovaleva, D. A. Kulikov

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Calculation of Water Saturation of Dolomite Reservoir Based on Multi-Pore Structure Model by Xinzhong Qi, Xingneng Wu, Yong Ai, Ruokun Huang, Wenxing Duan, Yaqi Liu

“…The above method is applied to dolomite reservoir saturation interpretation and reservoir evaluation. The coefficient of correlation for the nonlinear regression model is 0.668.…”
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Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction by Yonghong He, Pengwei Jin, Xin Wang, Shaoluo Shen, Jun Ma

“…To address the issue of insufficient prediction accuracy in traditional GM(1,1) models caused by significant nonlinear fluctuations in time-series data for ancient building structural health monitoring, this study proposes a wavelet decomposition-based GM(1,1)-BP neural network coupled prediction model. …”
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Modeling of settlement of shallow-founded rocking structures using explainable physics-guided machine learning by Sivapalan Gajan, Christopher Kantor

“…This paper examines the application of physics-guided machine learning (PGML) technique to model the settlement of shallow-founded rocking structures during earthquake loading. …”
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Modeling of the"thin" structure probability discrepancy distribution in the indications of ADS-B and SSR. Uncompensated latency by I. V. Alipov, V. L. Kuznetsov

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