Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

“…However, developing highly accurate and universal data- driven models using time-series analysis methods to achieve precise evaporation estimation remains a challenging. …”
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HEURISTIC SYNTHESIS ALGORITHM OF EVENT DEPENDENCIES MODEL by Dmitry V. Gorishny

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Population Median Estimation Using Auxiliary Variables: A Simulation Study with Real Data Across Sample Sizes and Parameters by Umer Daraz, Fatimah A. Almulhim, Mohammed Ahmed Alomair, Abdullah Mohammed Alomair

“…Through simulation studies and the analysis of various data sets, the performance of the proposed estimators is compared to existing methods. …”
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Deriving Early Citrus Fruit Yield Estimation by Combining Multiple Growing Period Data and Improved YOLOv8 Modeling by Menglin Zhai, Juanli Jing, Shiqing Dou, Jiancheng Du, Rongbin Wang, Jichi Yan, Yaqin Song, Zhengmin Mei

“…Combining multi-growth period data for crop analysis is of great significance for crop growth detection and early yield estimation. …”
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DEVELOPMENT OF SOFTWARE FOR EVALUATION OF DEFECT-FREE MANUFACTURE OF BAKERY PRODUCTS by Beznosov Y.V., Erdakova V.P., Poznyakovskiy V.M.

“…In the age of information technologies, modern management calls on producers to analyze not only quality errors but the data collected that allows you to see the frequency of occurrence of certain defects. …”
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A comparison between S-N Logistic and Kohout-Vechet formulations applied to the fatigue data of old metallic bridges materials by Joelton Fonseca Barbosa, Jos� A.F.O. Correia, Pedro A. Montenegro, Raimundo Carlos Silverio Freire J�nior, Grzegorz Lesiuk, Ab�lio M.P. De Jesus, Rui A.B. Cal�ada

“…Using a qualitative methodology of graphical adjustment analysis and another quantitative using the mean square error, it was possible to evaluate the performance of the mean S-N curve formulation. …”
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Intraosseous access: a simulation analysis by Antov Miki, Bartolomeo Rinaldi, Bergesio Giorgio, Vallana Vittoria, Roasio Agostino

“…Among nurses and students, data of the success of the procedure show significant results, but the difference between subgroups is still lower than expected considering  the results of the statistical analysis about procedure success, execution time and error percentage. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…Multidimensional analysis diagrams (e.g., residual distribution, 45° diagonal error plot, and boxplots) further validate the model’s robustness in different spatial locations, particularly in capturing abrupt changes and low-concentration anomalies. …”
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Longitudinal Motion System Identification of a Fixed-Wing Unmanned Aerial Vehicle Using Limited Unplanned Flight Data by Nuno M. B. Matos, André C. Marta

“…Acquiring knowledge of aircraft flight dynamics is crucial for simulation, control, mission performance and safety assurance analysis. In the fast-paced UAV market, long flight testing campaigns are hard to achieve, leaving limited controlled flight data and a significant amount of unplanned flight data. …”
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DA-IRRK: Data-Adaptive Iteratively Reweighted Robust Kernel-Based Approach for Back-End Optimization in Visual SLAM by Zhimin Hu, Lan Cheng, Jiangxia Wei, Xinying Xu, Zhe Zhang, Gaowei Yan

“…The method is compared with other robust function-based approaches via the EuRoC dataset and the KITTI dataset, showing adaptability across different VSLAM frameworks and demonstrating significant improvements in trajectory accuracy on the vast majority of dataset sequences. The statistical analysis of the results from the perspective of reprojection error indicates DA-IRRK can tackle non-Gaussian noises better than the compared methods.…”
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A comparison between S-N Logistic and Kohout-Věchet formulations applied to the fatigue data of old metallic bridges materials by Joelton Fonseca Barbosa, José A.F.O. Correia, Pedro Montenegro, Raimundo Carlos Silverio Freire Júnior, Grzegorz Lesiuk, Abílio M.P. De Jesus, Rui A.B. Calçada

“…Using a qualitative methodology of graphical adjustment analysis and another quantitative using the mean square error, it was possible to evaluate the performance of the mean S-N curve formulation. …”
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Data driven modeling of TiO2 PVP nanofiber diameter using LSTM and regression for enhanced functional performance by Harshada Mhetre, Sagar Pande, Babita Singla, Pavan Hiremath, Samriddh Sahu, Sarvesh Sorte, Ketan Kotecha, Nithesh Naik

“…TiO₂ + PVP nanofibers were fabricated under diverse conditions, including changes in applied voltage, solution concentration, and distance between tip to collector. The acquired data underwent analysis using LSTM and regression models to assess their predictive capabilities. …”
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Development of ann-based data-driven ground motion model for Azerbaijan using temporal earthquake records of 2022–2024 by T. Babayev, G. Babayev, S. Irawan, E. Bayramov

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Benchmark study of three statistical methods for six intact rock failure criteria constrained by different rock strength data by Peng-fei He, Xin Li, Xu-long Yao, Zhi-gang Tao, Yan-ting Du

“…Third, as the complexity of conventional test data increases or when true triaxial test data are used to estimate strength parameters for a three-dimensional failure criterion, it is essential to evaluate the outlier-proneness by analyzing the prediction error. …”
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Big data-driven corporate financial forecasting and decision support: a study of CNN-LSTM machine learning models by Aixiang Yang

“…The data underwent preprocessing and dimensionality reduction via Principal Component Analysis (PCA) to eliminate redundancy and noise. …”
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Research of Recognition Method of Discrete Wavelet Feature Extraction and PNN Classification of Rats FT-IR Pancreatic Cancer Data by Chayan Wan, Wenqing Cao, Cungui Cheng

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Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data by Pamelas M. Okoma, Siraj Ismail Kayondo, Ismail Y. Rabbi, Patricia L. Moreno-Cadena, Patricia L. Moreno-Cadena, Gerrit Hoogenboom, Gerrit Hoogenboom, Jean-Luc Jannink, Jean-Luc Jannink

“…Our experience suggests both that CGM calibration could become a routine component of the cassava breeding data analysis cycle and that there are opportunities for model improvement.…”
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Can linear regression modeling help clinicians in the interpretation of genotypic resistance data? An application to derive a lopinavir-score. by Alessandro Cozzi-Lepri, Mattia C F Prosperi, Jesper Kjær, David Dunn, Roger Paredes, Caroline A Sabin, Jens D Lundgren, Andrew N Phillips, Deenan Pillay, EuroSIDA Study, United Kingdom CHIC/United Kingdom HDRD Study

“…<h4>Background</h4>The question of whether a score for a specific antiretroviral (e.g. lopinavir/r in this analysis) that improves prediction of viral load response given by existing expert-based interpretation systems (IS) could be derived from analyzing the correlation between genotypic data and virological response using statistical methods remains largely unanswered.…”
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Distribution of Temperature and Total Suspended Solids (TSS) Of Lake Buyan Water Based On Pan-Sharpening Landsat 8 Data by Tolhas Tomu Tumeang, I Made Yuliara, I Gde Antha Kasmawan

“…The lowest temperature was recorded at the 1st and 2nd points, each at 25.00 0C, while the highest temperature was at the 28th to 30th points with a value of 26.00 0C. Analysis of the correlation between Landsat 8 data and in situ data produces a strong positive correlation for band 10 (0.7005) and a strong negative correlation for band 11 (0.4602). …”
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Effect of a surgical sponge counting stand on counting discrepancies, time efficiency, and operating room staff satisfaction: A quality improvement study by Naeimeh Eftekhari, Akram Aarabi, Aygineh Hairabedian

“…Data analysis was performed using SPSS version 16, employing descriptive statistics, paired t-tests, and Wilcoxon tests with a significance level set at 0.05.Results: The surgical sponge counting stand significantly reduced the time required for sponge counting during tissue closure (P<0.001) and skin closure (P<0.001), and significantly decreased overall counting discrepancies (P=0.01). …”
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