Estimation of Magnet Temperature Using Disturbance Observers of Permanent Magnet Synchronous Motor for Driving Single Rotary Compressor Without Lookup Table by Seoyun Lee, Jeonghyeok Kim, Hojun Kim, Dongho Kim, Jinyoung Choi, Hyun-Sam Jung

“…These results confirm the robustness, computational efficiency and feasibility of the proposed method, making it suitable for low-cost embedded systems in household appliances.…”
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Enhancing Visitor Forecasting with Target-Concatenated Autoencoder and Ensemble Learning by Ray-I Chang, Chih-Yung Tsai, Yu-Wei Chang

“…Extensive experiments conducted on the Taiwan and Hawaii datasets demonstrate that the proposed TCA method significantly outperforms traditional feature selection techniques and other advanced algorithms in terms of the mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R²). …”
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3D rock strength prediction by an innovative approach that integrates geostatistics with machine deep learning models by Hichem Horra, Ahmed Hadjadj, Elfakeur Abidi Saad, Khalil Moulay Brahim

“…The developed deep learning models achieved coefficient of determination values ranging from 0.9 to 0.99, demonstrating excellent predictive capability. …”
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A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…Experimental results indicate substantial improvements in key metrics including the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²), with R² values consistently exceeding 99.4% and achieving over 5% enhancement compared to the baseline GRU model. …”
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Income and wealth distribution in the European Union and Russia: comparativ analysis by E. R. Ermakova, I. E. Ilyakova

“…The methods of research are philosophical (dialectical, critical), general scientific (methods of scientific abstraction, the unity of the historical and logical, analysis and synthesis, induction and deduction, analogy, classification), private scientific (economic and mathematical, statistical, functional). …”
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Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating by N. Radhika, M. Sabarinathan, S. Sivaraman

“…Hyperparameter optimization is performed using the random search technique and is compared with the conventional grid search method. The hybrid ensemble technique demonstrates exceptional predictive performance, achieving a coefficient of determination (R2) of 0.92 with a Root Mean Square Error (RMSE) of 2.01 % and a Mean Absolute Error (MAE) of 1.62 % for porosity prediction, and R2 of 0.94 with the RMSE of 82.03 HV and MAE of 66.42 HV for hardness prediction. …”
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Developing a simple artificial intelligence fuzzy-based model for estimating saturated hydraulic conductivity of soil by Mohammad Naderianfar

“…In these models, saturated hydraulic conductivity was estimated using soil texture characteristics (percentage of clay, silt, and sand) and bulk density, and the performance of the models was evaluated using statistics such as root mean square error (RMSE), mean bias error (MBE), and coefficient of determination (R2). Comparing the results of the proposed nonlinear models with different input parameters showed that fuzzy systems can estimate saturated hydraulic conductivity with acceptable accuracy. …”
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The role of hybrid models in financial decision-making: Forecasting stock prices with advanced algorithms by Xiaoyi Zhu

“…This approach allowed the model to generalize effectively across a variety of global indices, as demonstrated by its high prediction accuracy (coefficient of determination (R2) values exceeding 0.98 for the Dow Jones, CSI, Nikkei, and DAX indices). …”
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Impact of Learning Motivation and Physical Condition on Physical Education Learning Outcomes in Junior High School Students Aged 13-15 Years: A Analysis studies by Muhammad Fikri, Dedi Nofrizal, Agung Nugroho, Hafiz Yazid Lubis

“…Results. The coefficient of correlation for rx12y = 0.49 is indicated. …”
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Measurement of Suspended Sediment Concentration at the Outlet of the Yellow River Canyon: Using Sentinel-2 Images and Machine Learning by Genxin Song, Youjing Jiang, Xinyu Lei, Shiyan Zhai

“…Results show that the model achieved a high coefficient of determination (R² = 0.94) and met accuracy requirements considering the maximum SSC, MAPE, and RMSE. …”
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SBNNR: Small-Size Bat-Optimized KNN Regression by Rasool Seyghaly, Jordi Garcia, Xavi Masip-Bruin, Jovana Kuljanin

“…The outcomes exhibit an enhancement of up to 5% in the coefficient of determination (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> score) using the proposed method compared to the standard KNN method optimized through grid search.…”
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THE EFFECT OF AN ANTI-TUMOR NECROSIS FACTOR-? AGENT ON DISEASE ACTIVITY,BLOOD RHEOLOGICAL PROPERTIES, AND THE ARTERIAL WALL IN PSORIATIC ARTHRITIS by Tatiana Viktorovna Korotaeva, E Yu Loginova, D S Novikova, L N Denisov, E S Mach, N V Klimova, A A Novikov, Sh F Erdes, N N Firsov

“…Erythrocyte aggregation (EA) parameters [Т1 (sec), Kt (c.u.); (sec-1), I2,5 (%)] were measured recording the rate of inverse light scattering and the levels of blood lipids [total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG)], and atherogenicity coefficient (AC) by routine methods on an automated Express plus analyzer (Bayer, Germany) at baseline, 4, and 12 weeks. …”
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The Role of Computed Tomography in Achieving True External Rotation in Robotic Knee Replacement: A Retrospective Analysis of 300 Knees by Pramod Bhor, Sawankumar Pawar, Syed Ali, Arvind Vatkar, Sachin Kale, Dnyanada Kutumbe

“…Intraclass correlation coefficient for the angle is 1 (TEA) and 0.98 (PCA). …”
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Applicability of Anisotropic Failure Criteria and Associated Application with Layered Rocks by Wenxue Deng, Tianhong Yang, Honglei Liu, Feiyue Liu, HongLiang Xu

“…Nonlinear least squares and traversing methods are used to determine the global minima of the material coefficients in the two types of functions. …”
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Prediction of Temporal Liking from Temporal Dominance of Sensations by Using Reservoir Computing and Its Sensitivity Analysis by Hiroharu Natsume, Shogo Okamoto

“…The trained models exhibited prediction accuracy of the determination coefficient as high as 0.676–0.993, with the median being 0.951. …”
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Ultra violet spectrophotometric analysis of Paracetamol, Diclofenac and Tramadol drugs in mixture by Eesa M. Thalij, Sarhan A. Salman, Hasan. M. Hasan

“…The method was compared with standard curved method, showed that it is obeyed Beer – lambert law in the concentration range of 0.1–1 µg/ml for standard addition and standard curve methods, with a correlation coefficient of 0.9980 and o.9944. …”
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Impact of morphological traits and irrigation levels on fresh herbage yield of sorghum x sudangrass hybrid: Modelling data mining techniques. by Halit Tutar, Senol Celik, Hasan Er, Erdal Gönülal

“…Model fit statistics, including coefficient of determination (R2), adjusted R2, root of mean square error (RMSE), mean absolute percentage error (MAPE), standard deviation ratio (SD ratio), Mean Absolution Error (MAE) and Relative Absolution Error (RAE), were used to evaluate the prediction abilities of the fitted models. …”
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Very good partial remission predicts progression-free survival in patients with multiple myeloma by A. S. Luchinin, S. V. Semochkin

“…The study used Spearman’s weighted correlation and linear regression methods to analyze the association between median PFS and VGPR+. …”
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Integrating Environmental Variables into Geostatistical Interpolation: Enhancing Soil Mapping for the MEDALUS Model in Montenegro by Stefan Miletić, Jelena Beloica, Predrag Miljković

“…The results were validated by the coefficient of determination (R²) and root mean square error (RMSE). …”
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Methodology of conducting experimental studies to assess qualitative and quantitative indicators of drawing prism formation by P. A. Grigorev, L. A. Sladkova

“…The method of processing the results of the experiment made it possible to qualitatively identify and quantitatively assess the process of formation of the drag prism when moving soil on the surface of the working body in two-dimensional space, to determine the change in the velocities of soil movement at an arbitrary point of the surface and to verify the working hypothesis and theoretical studies on the nature of the change in the velocities of soil movement in front of the dump surface.Discussions and conclusions. …”
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