Multi-Airport Capacity Decoupling Analysis Using Hybrid and Integrated Surface–Airspace Traffic Modeling by Lei Yang, Yilong Wang, Sichen Liu, Mengfei Wang, Shuce Wang, Yumeng Ren

“…We propose an integrated surface–airspace model. In the surface model, we utilize linear regression and random forest regression to model unimpeded taxiing time and taxiway network delays due to sparsity of ground traffic. …”
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Comparative evaluation of machine learning models for extreme river water level forecasting in Bangladesh: Implications for flood and drought resilience by Md Touhidul Islam, Sujan Chandra Roy, Nusrat Jahan, Al-Mahmud, Md Mazharul Islam, Abdullah Al Ferdaus, Kazunori Fujisawa, A.K.M. Adham

“…Performance was assessed using ten metrics including RMSE, R2, and NSE. Random Forest Regression (RFR) consistently outperformed other models, achieving the highest accuracy for both maximum (RMSE: 0.64–0.77 m; R2: 0.87–0.92) and minimum water levels (RMSE: 0.49–0.66 m; R2: 0.82–0.92), while linear models underperformed in capturing nonlinear patterns. …”
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The study of the relationship between physical activity and gestational diabetes mellitus in the second trimester of pregnancy: a dose-response analysis with the restricted cubic s... by Liuwei Zhang, Liping Zuo, Shengjun Sun, Yijia Ren, Yi Gao, Xiaoyan Zhang, Lichao Sun

“…The dose-response analysis was conducted, and optimal cut-off values of PA for the prevention of GDM were determined using the restricted cubic spline (RCS) model. Additionally, univariate and multivariate logistic regression analyses were employed to validate the identified cut-off values. …”
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Development of methodological approaches to the formation of a risk-based model to minimize the prevalence of adverse reactions in drug application in medical organizations of Mosc... by E. V. Kuznetsova, M. V. Zhuravleva, I. A. Mikhailov, T. I. Kurnosova

“…As part of the modeling stage, the integral score of the risk of ARs was presented as a sum of values for individual risk factors. …”
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Empirical Modeling of the Carbonylation of Acetylene for the Synthesis of Succinic Anhydride Using Gas Ratio (CO/C₂H₂) by Collins Ubaka Mordi, Ipeghan Jonathan Otaraku, Ishioma Laurene Egun

“…The R² values were 0.9219, 0.9563, and 0.9874 for the data in quadratic, cubic, and quartic models. These findings with statistical tests showed that the quartic model is the best empirical model for explaining the observed data variance (by a margin of 98.74%). …”
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Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study by Tiansheng Xia, Kaiyu Han

“…Conclusion In this research, the first risk prediction diagnostic model for heavy metal-chronic bronchitis was developed, in which CatBoost model had the best performance, and it provides a referenceable prediction model for the screening of high-risk groups.…”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Interpretable Machine Learning for the German residential rental market – shedding light into model mechanics by Severin Bachmann

“…Specific features are identified that distinguish the models, suggesting that a more complex model, like XGB, handles dummy variables more adeptly. …”
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EFFECTS OF TEMPERATURE AND PERCENTAGE OF ORGANIC MODIFIER ON RETENTION AND SELECTIVITY IN RP-HPLC USING SOLVATION PARAMETER MODEL by M.R. Hadjmohammadi

“…Effects of temperature and percentage of organic modifier were studied on retention and selectivity in RP-HPLC using solvation parameter model. The system constants were determined by multiple linear regression analysis from experimental values in the retention factor for a group of different solutes with known descriptors by computer using the program SPSS/PC. …”
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Tree volume modeling of different poplar clones in plantations in the Vojvodina region by Pantić Damjan, Borota Dragan, Janjatović Živan

“…Due to this sampling structure, it was not possible to build models (tables) at the level of clone, alluvium, soil type and plant spacing, but they were built based on the combined data for the whole area (Vojvodina), with certain exceptions - for I-214 (clone spacing and plant form) by applying the Schumacher-Hall linear mixed hierarchical (cluster) model; for M1 (clone) by applying classical regression analysis and for Deltoid clones (clona-alluvium of the Sava, alluvium of the Danube) by ap­plying the mixed linear hierarchical model, as in the case of I-214. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…Linear regression and decision tree models exhibited suboptimal performance because of their limitations in capturing non-linear relationships and overfitting, respectively. …”
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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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Remote sensing-driven machine learning models for spatiotemporal analysis of coastal phytoplankton blooms under climate change scenarios by Siqi Wang, Shuzhe Huang, Yinguo Qiu, Xiang Zhang, Chao Wang, Nengcheng Chen

“…These models incorporate remote sensing data and key environmental variables from Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs under different climate change scenarios. …”
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Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms by Nurcan Öztürk

“…The accuracy of Jaya and TLBO methods has been determined and these methods have been carried out with four different functions: quadratic, exponential, linear and power. Some statistical indices have been applied to evaluate the performance of these models. …”
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Spatial occurrence-intensity modeling of dengue incidence in southernmost provinces of Thailand. by Apiradee Lim, Lumpoo Ammatawiyanon, Haris Khurram, Phattrawan Tongkumchum, Don McNeil

“…While at second, the intensity is determined by fitting a log-linear regression model for disease intensity after excluding zeros.…”
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Modelling the Effects of Intelligentization on the Economic Resilience of Rural Households in the Face of Climate Change (Case study: Ferdows, Boshrouyeh & Sarayan Counties) by Aliakbar Anabestani, Nabiollah Taheri, Pegah Moridsadat

“…Additionally, the Structural Equation Modelling (SEM) approach was utilized with the Partial Least Squares method in the SMART PLS 4 software to examine the effects of the variables.Finding: The results of this research showed that the smartness of villages, with the value of T (18.958) and the value of the path coefficient (0.741), has a positive effect on the economic resilience of rural households in the face of climate change. …”
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PTML models of self assembled ligand free nanoparticle catalysts for cross coupling reactions by Andrea Ruiz-Escudero, Zuriñe Serna-Burgos, Sonia Arrasate, Humberto González-Díaz

“…Among the ANN models, MLP (9:9-20-9-1:1) and RBF (9:9-70-1:1) regression models showed similar results, with test MAE of 5.9% and 5.8% respectively, and both showed test RMSE of 9.8%. …”
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Establishing a best fit model of finger length to occlusal vertical dimension among students of college of health sciences Bayero University Kano by Ikusika OF, Idon PI, Iwuchukwu AO, Zirra AF, Usman N

“…Objectives: This study aimed to develop a best fit model equation relating finger length to occlusal vertical. …”
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Participatory Project Implementation and Sustainability of Government Funded Projects a Case study of Parish Development Model in Kabale District, Uganda by Moses, Agaba, Turyasingura, John Bosco

“…An analysis of the data was done using a linear regression model. According to the findings of a regression study, participatory project implementation has a favorable impact on the effectiveness of parish development models in Kabale District (coef = -0.890, p-value = 0.000). …”
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Job characteristics model-based study of the intrinsic motivations for primary care practitioners by Shichao Zhao, Jing Ping, Hong Zhu, Wanting Ji, Yuyan Wang, Ying Wang

“…Objective: This study aimed to analyze the job characteristics of primary care practitioners within the framework of Job Characteristics Model, evaluate their effect of intrinsic motivations on various job performance, compare the impact of five job characteristic dimensions with extrinsic motivators such as salary on these performance, and offer policy suggestions to enhance the motivations for bettering performance of primary care practitioners. …”
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