Evaluation of Data Mining and Artificial Intelligence Methods to Predict Daily Precipitation by Yaseen Ahmed Hamaamin

“…In ANFIS modelling, for several input variables up to 6 variables, this study recommends using the grid partition method to divide variable ranges into membership functions. …”
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Relationship Between Household Consumption and Disaggregated Wealth Components in OECD Countries: Panel Data Analysis for the Period 2010-2017 by Ahmet Hamdi Yanık, Ahmet İncekara

“…Based on a thorough analysis of the relevant literature, it was decided that a consumption function based on the life-cycle hypothesis was very useful for this study. …”
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Utilizing a Transient Electromagnetic Inversion Method with Lateral Constraints in the Goaf of Xiaolong Coal Mine, Xinjiang by Yingying Zhang, Bin Xie, Xinyu Wu

“…Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. …”
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Dual effects of leptin in perioperative gas exchange of morbidly obese patients. by Michele Carron, Giovanna Ieppariello, Gabriele Martelli, Giulia Gabellini, Mirto Foletto, Egle Perissinotto, Carlo Ori

“…Leptin has shown positive effects on respiratory function in experimental settings. The role of leptin on perioperative respiratory function in morbidly obese patients has not been established. …”
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Improved Deflection Prediction Model for PSC Box Girder with Stay Cable System during Tensioning Phase by Gangnian Xu, Weimin Xu, Zhanhong Wang, Ruishuo Zhang

“…Uncertainty and sensitivity analysis are conducted for the Dongming Huanghe River Highway Bridge. An objective function is applied to select the optimal combination of random variables, and a modified model is established and verified for accuracy. …”
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Modelling Geographically Weighted Truncated Spline Regression Using Maximum Likelihood Estimation for Human Development Disparities by Laode Muhammad Saris, Henny Pramoedyo, Adji Achmad Rinaldo Fernandes

“…Among these, the Bi-Square weighting function performed the best, achieving a coefficient of determination of 99.999%, demonstrating the model’s capability to explain nearly all data variability effectively. …”
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THE STRUCTURE OF HAPPINESS REPRESENTATION FOR RUSSIAN AND AMERICAN REPRESENTATIVES by S. Yu. Zhdanova, A. V. Pecherkina, A. A. Strokanov

“…Statistical analysis of the data was based on the use of the coefficient of φ-angular Fisher transform, correlation coefficient φ, and cluster analysis.Results and scientific novelty. …”
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Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…The improved model comprises four functional components. The innovation of this study lies in several aspects. …”
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EM Algorithm in the Modified Slash Power Maxwell Distribution with an Application by Francisco A. Segovia, Yolanda M. Gómez, Héctor J. Gómez, Inmaculada Barranco-Chamorro, Héctor W. Gómez

“…We study its probability density function and some properties, such as moments, asymmetry and kurtosis coefficient. …”
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Adaptive Fractional-Order Nonsingular Fast Terminal Sliding Mode Control for Manipulators by Xin Zhang, Ran Shi

“…Secondly, in view of the problems of large chattering and slow convergence speed in the reaching stage, this paper designs a variable exponential power-reaching law (VEPRL), which has the ability to change the exponential coefficients according to the system state adaptively. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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Research and development of thick plate shape prediction system based on industrial big data by Yufei MA, Changxin LIU, Wei KONG, Jinliang DING

“…Thick plate shape is one of the important indicators to measure the quality of thick plate products.The timely prediction of the final plate shape in production is of great significance for adjusting the operation and control of thick plate production.In actual industrial production, thick plate data has many characteristics, such as multiple coupling information, large amount of redundant information, and multi-source heterogeneity of data.Combining the needs of thick plate shape prediction, a thick plate shape prediction system was designed and developed.The data dump function was used to filter and preprocess the industrial big data to remove the coupling information and redundant variables in the data.LSTM neural network, convolutional neural network and 3D convolutional neural network were used to extract data features from data of different dimensions, and the features were fused based on the maximum mutual information coefficient to establish an integrated learning prediction model, which effectively solved the modeling difficulties caused by multi-source heterogeneous data.The actual industrial data of a domestic thick plate production line was used for verification, and the results showed the effectiveness of the developed system.…”
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A Hybrid RBF-PSO Framework for Real-Time Temperature Field Prediction and Hydration Heat Parameter Inversion in Mass Concrete Structures by Shi Zheng, Lifen Lin, Wufeng Mao, Yanhong Wang, Jinsong Liu, Yili Yuan

“…Sensitivity analysis identified the ultimate adiabatic temperature rise as the dominant parameter (78% variance contribution), followed by synergistic interactions between hydration rate parameters, and indirect coupling effects of boundary correction coefficients. These findings guided a phased optimization strategy, as follows: prioritizing high-precision calibration of dominant parameters while relaxing constraints on low-sensitivity variables, thereby balancing accuracy and computational efficiency. …”
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Design and Simulation of Ornithopter based on Four-bar Mechanism by Zhao Zhifang, Qi Mingsi, Feng Jingkai, Zhang Wei, Wang Junyuan, Zhang Jiping

“…The brushless motor driving two stage reducer,provides input for four-bar mechanism. The robot has a function of the periodic flapping motion,the frequency change and size of the attitude angle adjustment. …”
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The Fuzzy Response Surface Reliability Analysis Method of Turbine Blades by PAN Cheng-yi, WEI Wen-long, ZHANG Chun-yi

“…The analysis result shows that the blade reliability indexes decrease with the increase of fuzzy coefficient. Compared with the traditional method based on random variables, this method is more reasonable for the description of uncertainty, and the evaluation of reliability is more accurate theoretically.…”
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A Particle Swarm Optimization-Guided Ivy Algorithm for Global Optimization Problems by Kaifan Zhang, Fujiang Yuan, Yang Jiang, Zebing Mao, Zihao Zuo, Yanhong Peng

“…In recent years, metaheuristic algorithms have garnered significant attention for their efficiency in solving complex optimization problems. …”
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Which Metrics Can I Monitor? Test-Retest Reliability of Countermovement Jump and Countermovement Rebound Jump Force-Time Metrics in Youth Soccer Players In-Season by Andrew Badby, Paul Comfort, Nicholas Ripley, Matthew Cuthbert, Francisco Robles-Palazón, Peter Mundy, John McMahon

“…Objective measures provide the most effective means of monitoring the magnitude and time course of changes in neuromuscular function (NMF) resulting from physical activity if measurements are repeatable (reliability). …”
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A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre-A phantom study. by Patrizio Barca, Fabio Paolicchi, Giacomo Aringhieri, Federica Palmas, Daniela Marfisi, Maria Evelina Fantacci, Davide Caramella, Marco Giannelli

“…CT image quality for each scanner/acquisition protocol was assessed through noise level, noise power spectrum (NPS), contrast-to-noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD) and non-uniformity index analyses. …”
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Sensitivity analysis of melting heat transfer in Williamson fluid by Aliya Batool, Zakir Hussain, Dilawar Hussain

“…The model is simplified to ordinary differential equations by introducing similarity variables and tackled by bvp4c Matlab function. The significant variables on flow model are identified by Response Surface Method (RSM). …”
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Sensitivity to Instruction Strategies in Motor Learning Is Predicted by Anterior–Posterior TMS Motor Thresholds by Michael L. Perrier, Kylee R. Graham, Jessica E. Vander Vaart, W. Richard Staines, Sean K. Meehan

“…Recent transcranial magnetic stimulation (TMS) studies suggest that variability in interneuron recruitment by anterior–posterior (AP) currents is linked to differences in functional connectivity between premotor and motor regions. …”
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