Comparison of the Regression Method and The Neural Network Method in Specific Cases of Engineering Practice by Križan Peter, Svátek Michal, Matúš Miloš, Hanko Lukáš

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Optimizing photovoltaic thermal systems with ternary hybrid nanofluids: Statistical and regression analysis by Ahmad Ayyad Alharbi, Ali Rashash Alzahrani

“…It encompasses a broad array of numerical, statistical, and regression analyses to delve into the electrical, thermal, and phase transition characteristics of paraffin wax. …”
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Rationale of the multidimensional nonlinear REGRESSION MODEL of the PARAMETERS of bridge crane's WORKING PROCESS by V. S. Shcerbakov, M. S. Korytov, M. Y. Arkhipenko, E. O. Volf

“…It is concluded that the complexity of the regression expression by increasing the number of its items beyond 12 doesn’t lead to further increasing the accuracy of approximation.…”
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Regression Analysis to Predict the Length of Time to Complete a Thesis based on the Title by Al Aminuddin, Rahmat Hidayat, Gita Sastria, Astried Astried

“…In general, the difficulty or complexity of the thesis can be reflected through the title of the thesis that is appointed. …”
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Cleaning of Abnormal Wind Speed Power Data Based on Quartile RANSAC Regression by Fengjuan Zhang, Xiaohui Zhang, Zhilei Xu, Keliang Dong, Zhiwei Li, Yubo Liu

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Standardised regression coefficient as an effect size index in summarising findings in epidemiological studies by Pentti Nieminen, Heli Lehtiniemi, Kirsi Vähäkangas, Antti Huusko, Arja Rautio

“…</p><p><strong>Methods:</strong> we outline the complexities involved in synthesising associations. We describe a method by which it is possible to transform the findings into a common effect size index which is based on standardised regression coefficients. …”
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Preoperative kidney tumor risk estimation with AI: From logistic regression to transformer. by Vesna Barros, Nour Abdallah, Michal Ozery-Flato, Avihu Dekel, Moshiko Raboh, Nicholas Heller, Simona Rabinovici-Cohen, Alex Golts, Amilcare Gentili, Daniel Lang, Suman Chaudhary, Varsha Satish, Resha Tejpaul, Ivan Eggel, Itai Guez, Ella Barkan, Henning Müller, Efrat Hexter, Michal Rosen-Zvi, Christopher Weight

“…Second, interobserver variability is large. These complexities encourage the use of computational models as accurate noninvasive tools to find relevant relationships between individual perioperative renal mass characteristics and patient risk. …”
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Assessing the impact on quality of prediction and inference from balancing in multilevel logistic regression by Carolina Gonzalez-Canas, Gustavo A. Valencia-Zapata, Ana Maria Estrada Gomez, Zachary Hass

“…The primary goal of this research is to examine the impact of balancing data on the prediction quality and inference in multilevel logistic regression models. Logistic regression is a valuable approach for modeling binary outcomes expected in health applications. …”
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Apply Ridge Regression Model to Predict the Lateral Velocity Difference of Tight Reservoirs by HAN Longfei, ZHANG Yongfei, WANG Miaomiao, LI Yu

“…The random forest algorithm is used to rank the influence factors, and the vertical wave time lag, bulk density, and compensated neutron logging curves are selected as the input parameters of the lateral wave time lag prediction model to reduce the complexity of the model. Finally, a ridge regression algorithm is used to establish a prediction model of the lateral wave time lag based on the logging data of five wells in WQ block. …”
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The diagnostic conundrum of late-onset developmental regression in child psychiatry: case series by Shalu Elizabeth Abraham, Sakhardande Kasturi Atmaram, Poornima Khadanga, Nirmalya Mukherjee, Rajendra Kiragasur Madegowda, Harshini Manohar

“…The complexity is further compounded when it is associated with psychotic symptoms. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…A random forest (RF) model, interpreted with Shapley Additive exPlanations (SHAP) and Partial Dependence Plot (PDP) algorithms, explores nonlinear driving mechanisms, while Geographically and Temporally Weighted Regression (GTWR) assesses drivers’ spatiotemporal heterogeneity. …”
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Complex Treatment for Sterile Pancreonecrosis by Yu. V. Nikiforov, S. V. Mikhailusov, Ye. V., Moiseyenkova, A. Yu. Yudin, A. V. Vorykhanov, A. V. Chirkov

“…The diagnosis of SPN was established by a complex of clinical, biochemical, and instrumental studies (abdominal ultrasonography, gastroduodenoscopy, if needed, diagnostic laparoscopy). …”
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Reliability and Quality of Complex Systems by I.E. Starostin, S.I. Gavrilenkov

Reliability and Quality of Complex Systems by A.N. Litvinov

A Penalized h-Likelihood Variable Selection Algorithm for Generalized Linear Regression Models with Random Effects by Yanxi Xie, Yuewen Li, Zhijie Xia, Ruixia Yan, Dongqing Luan

“…Reinforcement learning algorithms present a major challenge in complex dynamics recently. In the perspective of variable selection, we often come across situations where too many variables are included in the full model at the initial stage of modeling. …”
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The Influence of Equity Market Sentiment on Credit Default Swap Markets: Evidence from Wavelet Quantile Regression by Weifang Mao, Huiming Zhu, Hao Wu, Zhongqingyang Zhang, Jin Chen

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Evolocumab Added to Statin Is Associated With Intracranial Atherosclerotic Plaque Regression Compared With Statin Alone by Xinzhi Hu, Yiyang Liu, Weizhuang Yuan, Zongmuyu Zhang, Shun Li, Anqi Cheng, Qiuyu Yu, Haoyao Guo, Yinxi Zou, Mingli Li, Caiyan Liu, Yan Xu, Weihai Xu

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Arctic tern-optimized weighted feature regression system for predicting bridge scour depth by Jui-Sheng Chou, Asmare Molla

“…This paper presents a pioneering artificial intelligence (AI) solution – the Arctic Tern-Optimized Weighted Feature Least Squares Support Vector Regression (ATO-WFLSSVR) system to aid civil engineers in accurately predicting scour depth at bridges. …”
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A Hybrid Approach to Modelling ECC Risk: Effectiveness of Nonparametric Regression and MLFNN Techniques by Fei Hong Seng, Wan Muhamad Amir W Ahmad, Mohamad Nasarudin Adnan, Farah Muna Mohamad Ghazali, Nor Azlida Aleng

“…Integrating nonparametric regression and MLFNN validation provides a robust framework for modelling ECC risk, capturing complex nonlinear relationships between family size and anthropometric factors. …”
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Regression analysis and artificial neural networks for predicting pine species volume in community forests by Wenceslao Santiago-García

“…Destructive sampling provided data from 56 P. patula and 51 P. pseudostrobus trees, covering a wide range of diameters and heights. The regression approach employed seemingly unrelated nonlinear regression (NSUR) to fit simultaneous additive volume systems using both one- and two-variable models. …”
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