Research on dynamic evaluation method of individual scientific impact under multiple key nodes by Shuang Ma

Subjects: “…two-node piecewise linear regression model…”
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Impact of landscape patterns on river water quality: Spatial-scale effects across an agricultural-urban interface by Kun Mei, Haonan Shi, Yupeng Wu, Randy A. Dahlgren, Xiaoliang Ji, Minmin Yang, Yueru Guan

Subjects: “…Stepwise multiple linear regression model (SMLR)…”
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A Novel Output Prediction Method in Production Management Based on Parameter Evaluation Using DHNN by Jiantao Chang, Yuanying Qiu, Xianguang Kong

“…To overcome this difficulty, a dynamic-improved multiple linear regression model based on parameter evaluation using discrete Hopfield neural networks (DHNN) is presented. …”
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Regression Cloud Models and Their Applications in Energy Consumption of Data Center by Yanshuang Zhou, Na Li, Hong Li, Yongqiang Zhang

“…The experiments show that linear regression model is good enough to model performance counters, nonlinear regression is better than linear regression model for modeling system utilization, and support vector regression model is better than polynomial and exponential regression models.…”
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Haptoglobin Genotype and Risk Markers of Cardiovascular Disease in Patients with Chronic Kidney Disease by Charlotte Strandhave, My Svensson, Henrik Krarup, Jeppe Hagstrup Christensen

“…In an adjusted linear regression model, Hp 2-2 was associated with both SDNN (P=0.005) and SDANN (P=0.01). …”
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Mathematical modelling criminality in Lithuania in a context of the East European countries by Vitalija Rudzkienė

“…The analysis of differences between the criminality in Lithuania and the average criminality rates in Bulgaria, Hungary and Poland is fulfilled using linear regression model. …”
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A nonlinear correlation between the serum uric acid to creatinine ratio and the prevalence of hypertension: a large cross-sectional population-based study by Ru Wang, Shuxing Wu, Jing Wang, Wenting Li, Jian Cui, Zhuhua Yao

“…Further threshold effect showed that only a UA/Cr ratio less than 5.0 was related to hypertension risk (OR: 1.178, 95% CI: 1.086-1.278, p < 0.001), and the 2-piecewise linear regression model was superior to the 1-line linear regression model (p < 0.05).Conclusion The UA/Cr ratio was associated with the prevalence of hypertension.…”
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Quantification of Rear-End Crash Risk and Analysis of Its Influencing Factors Based on a New Surrogate Safety Measure by Qiangqiang Shangguan, Ting Fu, Junhua Wang, Rui Jiang, Shou’en Fang

“…Then, a mixed-effects linear regression model was applied to clarify the relationship between rear-end crash risk and its influencing factors. …”
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Machine learning-driven solar irradiance prediction: advancing renewable energy in Rajasthan by Aayushi Tandon, Amit Awasthi, Kanhu Charan Pattnayak, Aditya Tandon, Tanupriya Choudhury, Ketan Kotecha

“…This model outperforms the Linear Regression model by a notable 19.47%, highlighting its superior predictive abilities. …”
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Types of tourists and tourism practices during the Olympic Games. by Marie Delaplace, Alexandra Schaffar

“…The statistical analyses conducted on the data obtained (multiple component analysis, dendrogram and linear regression model) allow us to characterize both the tourists who will come and those who will not as well as their respective practices, in particular concerning the visited sites.…”
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On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression by Chaolin Liu, Hu Yang, Jibo Wu

“…We introduce the weighted mixed almost unbiased ridge estimator (WMAURE) based on the weighted mixed estimator (WME) (Trenkler and Toutenburg 1990) and the almost unbiased ridge estimator (AURE) (Akdeniz and Erol 2003) in linear regression model. We discuss superiorities of the new estimator under the quadratic bias (QB) and the mean square error matrix (MSEM) criteria. …”
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The Relationship Between Novel Inflammatory Markers and Serum 25‐Hydroxyvitamin D Among US Adults by Hang Zhao, Yangyang Zhao, Yini Fang, Weibang Zhou, Wenjing Zhang, Jiecheng Peng

“…A multivariable linear regression model assessed the links between serum 25(OH)D and these novel inflammatory markers, with subgroup analyses for hypertension and diabetes. …”
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DIGITALIZATION OF ECONOMICS AND DEVELOPMENT BANKS: PROSPECTS FOR EVALUATION ON THE EXAMPLES OF THE RUSSIAN FEDERATION AND VEB.RF by S. S. Matveevskii, N. N. Agafonova

“…The experience of using digitalization indexes to assess the digitalization level of the economy has been summarized: it is advisable to use interval indexes that allow us to divide countries into groups according to the digitalization level. Using the linear regression model developed by the authors has made it possible to establish a direct statistical relationship between the I-Desi digitalization index and per capita Gross Domestic Product for a number of developed and developing countries: more developed countries carry out digitalization faster. …”
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Is There a Seasonal Difference in the Detection of Trichomonas vaginalis by Cervical Cytology? by Sydney Shrader, Enrique Hernandez, John Gaughan

“…The occurrence of a diagnosis of T. vaginalis was analyzed by year, by quarter, and by month using a generalized linear regression model. The prevalence of a T. vaginalis diagnosis during the 6-year study period was 3.1%. …”
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Modeling of River Sediment Estimation Using Artificial Neural Network Method (Case Study: Vanai River) by Dariush Abolfathi, Aghil Madadi, Sayyad Asghari

“…Evidence has shown that initially the MLP's neural network model had the best estimate with the lowest error rate (90.44) and then the RBF model (151.44) among the three models. The linear regression model has the highest error rate because only linear relationships between variables are considered.…”
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Multipoint Vibration Response Prediction under Uncorrelated Multiple Sources Load Based on Elastic-Net Regularization in Frequency Domain by ZhenKai Cui, Cheng Wang, Jianwei Chen, Ting He

“…Firstly, a multi-input and multioutput linear regression model of the multipoint frequency domain vibration response is trained using historical data at each frequency point. …”
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Weaker Regularity Conditions and Sparse Recovery in High-Dimensional Regression by Shiqing Wang, Yan Shi, Limin Su

“…Based on both methods, we derive, in parallel, more precise bounds for the estimation loss and the prediction risk in the linear regression model when the number of variables can be much larger than the sample size.…”
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Parameter Study and Economic Efficiency Optimization for Laser Cladding with Wide-Band Fiber Laser by Bin Hu, Jianhai Han, Junhua Wang

“…The effects of the three process parameters on the geometry characteristics and economic efficiency of single tracks were statistically analyzed, and a linear regression model was established between the combined parameters and the relevant characteristics (including track height, ratio of track width to height, powder efficiency, and deposition speed). …”
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Financial Accountability and Service Delivery in Kabale District, Uganda by Biryomumaisho Ferdison, Turyasingura John Bosco, moses Agaba, Vicent Miganda

“…At the bivariate level, a Pearson correlation matrix was conducted to ascertain the relationships between the predictor variables and the dependent variable. A linear regression model was used to fit the data. Research findings from the regression model show that funds disbursement (R=862), Auditing process (R=656 and record-keeping systems (R=899) have a positive significance on the service delivery of Kabale District local government. …”
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Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis by Renfu Jia, Shibiao Fang, Wenrong Tu, Zhilin Sun

“…In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. …”
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