Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…On this basis, we selected three nonlinear machine learning models (XGBoost, RFR, SVR) and one multiple linear regression model (PLSR) to construct the LCC inversion model, and we chose the optimal model to generate spatial distribution maps of maize LCC at the regional scale. …”
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Multi-Criteria Assessment of Flood Risk on Railroads Using a Machine Learning Approach: A Case Study of Railroads in Minas Gerais by Fernanda Oliveira de Sousa, Victor Andre Ariza Flores, Christhian Santana Cunha, Sandra Oda, Hostilio Xavier Ratton Neto

“…The models evaluated included linear regression, random forest, decision tree, and support vector machines. …”
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Multi-objective optimization of an open-pit mining system to determine safety buffer using the modified NBI method and the meta-model approach by Tahereh Khajvandsany, Hossein Amoozad Khalili, Ramezan Rezaeyan, Kourosh Nemati

“…A quadratic nonlinear regression model was determined for the objectives of maximizing the amount of sulfide rock extraction and minimizing the total costs of the haulage system and a linear regression model for the objective of maximizing the total rock loaded on trucks. …”
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Industrial multi-machine data aggregation, AI-ready data preparation, and machine learning for virtual metrology in semiconductor wafer and slider production by Feiyang Ou, Julius Suherman, Chao Zhang, Henrik Wang, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…Advanced machine learning techniques are used to tackle the modeling challenges of a low failure rate and limited operational variability. XGBoost, a gradient descent-based tree algorithm, outperforms the commonly used Feedforward Neural Networks (FNN) in terms of training speed and resource utilization for binary-classifications, as well the performance criterion in ROC-AUC score (classification), Median Absolute Error (regression) and R2 value. …”
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Exploring the Determinants of Spatial Vitality in High-Speed Rail Station Areas in China: A Multi-Source Data Analysis Using LightGBM by Pengpeng Liang, Xu Cui, Jiexi Ma, Wen Song, Yao Xu

“…This study investigates 66 HSR station areas in 35 Chinese cities by integrating multi-source data—Sina Weibo check-in records, urban support indicators, station attributes, and built environment variables—within a city–node–place analytical framework. …”
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Spatiotemporal Dynamics and Response of Land Surface Temperature and Kernel Normalized Difference Vegetation Index in Yangtze River Economic Belt, China: Multi-Method Analysis by Hongjia Zhu, Ao Wang, Pengtao Wang, Chunguang Hu, Maomao Zhang

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AI-driven analysis by identifying risk factors of VL relapse in HIV co-infected patients by Abhishek Kumar, Sanchita Mondal, Debnarayan Khatua, Debashree Guha, Budhaditya Mukherjee, Arista Lahiri, Dilip K. Prasad, Arif Ahmed Sekh

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Multi-Decision Vector Fusion Model for Enhanced Mapping of Aboveground Biomass in Subtropical Forests Integrating Sentinel-1, Sentinel-2, and Airborne LiDAR Data by Wenhao Jiang, Linjing Zhang, Xiaoxue Zhang, Si Gao, Huimin Gao, Lin Sun, Guangjian Yan

“…This study proposes a multi-source data integration framework using Sentinel-1 (S-1) and Sentinel-2 (S-2) data along with eight predictive models (i.e., multiple linear regression—MLR; Elastic-Net; support vector regression (with a linear kernel and polynomial kernel); k-nearest neighbor; back-propagation neural network—BPNN; random forest—RF; and gradient-boosting tree—GBT). …”
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Association between 24-hour urine volume and 28-day intensive care unit mortality in sepsis patients: a multi-center retrospective cohort study by Yuzhan Lin, Weiguo Lin, Cheng Fu, Ruixue Sun, WeiLi Hong, Xinglin Chen, Shaorong Yan

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Factors influencing high-risk fertility practices among women of childbearing age in Tanzania: using DHS 2022 by Hiwot Altaye Asebe

“…To deal with the survey’s clustered structure and the binary nature of the outcome variable, a multi-level mixed-effect generalized linear model (Poisson regression with robust error variance) was employed. …”
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Association of blood urea nitrogen with 28-day mortality in critically ill patients: A multi-center retrospective study based on the eICU collaborative research database. by Ting Deng, Die Wu, Shan-Shan Liu, Xing-Lin Chen, Zhen-Wei Zhao, Lan-Lang Zhang

“…The statistical analyses included univariate and multivariate logistic regression, as well as generalized additive modelling, which was employed to assess the non-linear relationship between BUN and mortality.…”
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Integrating univariate and multivariate stability indices for breeding clime-resilient barley cultivars by Ammar Elakhdar, Ahmed A. El-Naggar, Sally El-Wakeell, Anas H. Ahmed

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Maternal parity modifies the association of birthweight polygenic score with fetal growth by Prabhavi Wijesiriwardhana, Tesfa Dejenie Habtewold, Guisong Wang, Jessica L. Gleason, Ronald J. Wapner, Katherine L. Grantz, Fasil Tekola-Ayele

“…., change in fetal size over a 1-week gestational age interval) at gestational weeks 10–40 in two multi-ancestral cohorts of pregnant women. mGRS, derived from previously identified birthweight-reducing maternal variants was tested for association with fetal size and weekly growth pace using linear regression adjusted for fetal sex and top 10 genetic principal components. …”
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Mentalization-based treatment versus bona fide treatment for patients with borderline personality disorder in Germany (MAGNET): study protocol of a prospective, multi-centre random... by Sophie Hauschild, Svenja Taubner, Thorsten Vidalón Blachowiak, Ulrike Dinger, Harald Gündel, Sabine C. Herpertz, Jörg Rademacher, Bernhard Strauss, Timo Storck, Ralitsa Vassileva, Ina Burghaus, Manuel Herbst, Simiao Chen, Christoph Nikendei, Sebastian Euler, Jana Volkert

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Toward sustainable machining of hardened SKD11: Machine learning-based evaluation and optimization of surface roughness, tool wear, and CO2 emissions by Van-Canh Nguyen, Dung Hoang Tien, Van-Hung Pham, Thinh-Viet Nguyen, Thuy-Duong Nguyen

“…Experimental data collected according to a Box-Behnken matrix were utilized to develop linear and non-linear regression models. Results indicated that the second-order model demonstrated superior predictive accuracy for Ra (R² = 0.997) and CE (R² = 0.994), whereas the Vb prediction model failed to achieve sufficient reliability. …”
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Lis State of the Greenland and Barents Sea ice cover in the context of current climate change by Ye. U. Mironov, E. S. Egorova, N. A. Lis

“…To reveal the dependence of changes in the sea ice area on various hydrometeorological factors, statistical analysis with use of multi-regression models, namely the method of inclusion of variables, was applied. …”
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Development of Semiparametric Smoothing Spline Path Analysis on Cashless Society by Muhammad Rafi Hasan Nurdin, Muhammad Ohid Ullah, Adji Achmad Rinaldo Fernandes, Eni Sumarminingsih, Solimun Solimun

“…Parametric path analysis is appropriate when all variable relationships are linear. For entirely non-linear relationships, a nonparametric model can be used, while a semiparametric model applies if there is a mix of linear and non-linear relationships. …”
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Multivariate predictive modeling of compressive strength in ground granulated blast furnace slag/fly ash-based alkali-activated concrete by Dina A. Emarah

“…Unlike previous studies that often focus on a limited set of parameters or single-variable models, this work evaluates and compares four advanced predictive models: Linear Regression (LR), Multi-Linear Regression (MLR), Non-Linear Regression (NLR), and Artificial Neural Networks (ANN). …”
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Investigating the Impact of the Socio-Cultural Factors Effecting on Political Orientation in Ahvaz and Yasouj by Abdolah Fazeli, arman heydari, ramin moradi

“…The results of regression analysis showed that independent variables affect the dependent variable and in total explain about 41% of variance of dependent variable. …”
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Quantitative Analysis of the Determinants of NBA Player Performance and Market Value by Lin Chuhao

“…A multi-variable linear regression model was applied to evaluate how these metrics predict a player’s value. …”
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