Konsistensi Model Regresi Empat Variabel Pada Populasi dan Sampel untuk Prediksi Temperatur by Nurjannah Syakrani, Naufal Athaya S. R

Subjects: “…Multi Variable Linear Regression…”
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Multicriteria-based optimization and multi-variable non-linear regression analysis of concrete containing blends of nano date palm ash and eggshell powder as cementitious materials by Adamu Musa, Ibrahim Yasser E., Charpe Anuja U., Raut Ashwin Narendra

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Uncertainty Quantification and Sensitivity Analysis of Concrete Structure Using Multi-Linear Regression Technique by Abdelhamid Hebbouche, Salim Bennoud, Ayoub Zeroual

“…This paper shows computational analysis for the characterization of the behavior of a concrete gravity dam under seismic loads, which are considered sources of uncertainties. The multi-linear regression methodology was performed and applied to evaluate the dynamic response of the considered structure. …”
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Soil moisture estimation using multi linear regression with terraSAR-X data by G. García, M. Brogioni, V. Venturini, L. Rodriguez, G. Fontanelli, E. Walker, S. Graciani, G. Macelloni

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Multi-task genomic prediction using gated residual variable selection neural networks by Yuhua Fan, Patrik Waldmann

“…Methods This study aims to enhance genomic prediction by implementing gated residual variable selection neural networks (GRVSNN) for multi-task genomic prediction. …”
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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data. by Lulu Pan, Qian Gao, Kecheng Wei, Yongfu Yu, Guoyou Qin, Tong Wang

“…Extensive simulation experiments as well as an application demonstrate that Trans-PtLR demonstrates robustness and better performance of estimation and prediction when heavy-tail and outliers exist compared to transfer learning for linear regression model with normal error distribution. …”
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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing by Dapeng Chen, Hongbin Luo, Zhi Liu, Jie Pan, Yong Wu, Er Wang, Chi Lu, Lei Wang, Weibin Wang, Guanglong Ou

“…To this end, this study employed six types of remote sensing data—Landsat 8 OLI, Sentinel-2A, GEDI, ICESat-2, ALOS-2, and SAOCOM. A dual-variable selection strategy based on SHapley Additive exPlanations (SHAP) was developed, and a genetic algorithm (GA) was used to optimize the parameters of five machine learning models—elastic net (EN), least absolute shrinkage and selection operator (Lasso), support vector regression (SVR), Random Forest (RF), and Categorical Boosting (CatBoost)—to estimate the AGB of <i>Pinus kesiya</i> var. …”
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Cognitive biases and contextual factors explaining variability in nurses’ fall risk judgements: a multi-centre cross-sectional study by Miyuki Takase, Naomi Kisanuki, Yoko Sato, Kazue Mitsunaka, Masako Yamamoto

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Unsupervised feature selection based on generalized regression model with linear discriminant constraints by Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai

“…We reformulate our proposed method as a multi-variable optimization problem that incorporates equality constraints. …”
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Estimation of Beginning Points of Cross-Shore Sandbars Using Artificial Neural Network by Mert SABANCIOGLU, Mustafa DEMIRCI, Yunus Ziya KAYA

“…In this paper, beginning points of cross-shore sandbars predicted using artificial neural network (ANN), multi-linear regression (MLR), and Quadratic-Multivariable Regression (Q-MR). …”
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Bus driver deceleration behavior modeling at intersections using multi-source on-board sensor data by Yancheng Ling, Zhenliang Ma, Yuchen Song, Qi Zhang, Xiaoxiong Weng, Xiaolei Ma

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Spatiotemporal variability and trends in extreme rainfall and temperature indices in Southeastern Oromia, Ethiopia by Yared Tesfaye, Nigussie Dechassa, Yibekal Alemayehu, Dereje Ademe Birhan

“…Using data from nine meteorological stations, we analyzed spatiotemporal trends via the Modified Mann-Kendall test with Hamed and Rao’s autocorrelation correction, Theil–Sen slope estimator, descriptive statistics, linear regression, and Standardized Anomaly Index (SAI). …”
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The impacts of light rail on residential property values in a non-zoning city: A new test on the Houston METRORail transit line by Qisheng Pan

“…Similar to the previous studies, the author adopts a traditional ordinary linear regression (OLS) to investigate the contribution of a set of variables representing the physical, neighborhood, and accessibility characteristics of properties, and also employs a multi-level regression model (MLR) to examine the hierarchical structures of spatial data explicitly. …”
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Stature estimation and sex determination from contemporary Northeastern Thai clavicles using discriminant function and linear regression analyses by Chanasorn Poodendaen, Poonikha Namwongsakool, Sitthichai Iamsaard, Nareelak Tangsrisakda, Rarinthron Samrid, Chadaporn Chaimontri, Worrawit Boonthai, Suthat Duangchit

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Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis by Yun Liu, Yun Liu, Yun Liu, Xibin Han, Xibin Han, Xiaodong Cui, Xiaohu Li, Xiaohu Li, Haiyan Jin, Haiyan Jin

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Enhancing Manufacturing Processing Stability and Efficiency with Linear-Regression Analysis: Modeling on a Flow-Drill Screw (FDS) Joining Process by Chengxin Zhang, Mario Guzman, Xuzhe Zhao

“…To enhance the stability and efficiency of the screwing process, this study seeks multi-disciplinary collaboration by applying linear-regression modeling. …”
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Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control by Laila Nur Azizah, Adji Achmad Rinaldo Fernandes, Ni Wayan Surya Wardhani

“…This study aims to develop a multi-response semiparametric multi-group regression model using the truncated spline approach to understand the variables influencing rice pest control under light and dark conditions. …”
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Modeling the critical causal factors of postharvest losses in the vegetable supply chain in eThekwini metropolitan municipality: The log-linear regression model by Siphesihle Qange, Lelethu Mdoda, Asanda Mditshwa

“…The study adopted a cross-sectional research design and a multi-stratified random sampling method. Descriptive statistics and log-linear regression were used to analyze the data. …”
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Carcinogenic health risks and water quality assessment of groundwater around lead–zinc mining areas of Ebonyi state Nigeria: a data-driven machine learning approach by Obinna Chigoziem Akakuru, Moses Oghenenyoreme Eyankware, Godwin O. Aigbadon, Ayatu Ojonugwa Usman, Alexander Iheanyi Opara, Kizito Ojochenemi Musa, Micheal Akaninyene Okon, Okechukwu Pius Aghamelu, Gabriel Ehriga Odesa, Ifeyinwa Juliana Ofoh, Annabel U. Obinna-Akakuru

“…The Artificial Neural Networks, Support Vector Machines, and Multi-Linear Regression (MLR) models effectively predicted pollution indices, with MLR showing the most reliable performance (perfect R2 value). …”
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Intrapersonal day-to-day travel variability and duration of household travel surveys: Moving beyond the one-day convention by Wei Li, Douglas Houston, Marlon G. Boarnet, Han Park

“…Our analytical methods included linear regressions and random sampling experiments. …”
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