Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…The optimization targeted the perforation friction coefficient <italic>k</italic>_perf as the primary unknown variable. …”
Get full text

Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm by S. Sharifi, N. Hafezi, M. H. Aghkhani

“…In the first step, energy consumption and production were calculated by multiplying the variables by their corresponding coefficients. In the second step, all the variables that maximize paddy yield were entered into MATLAB software. …”
Get full text

Multi-objective design optimization of a transonic axial fan stage using sparse active subspaces by Richard Amankwa Adjei, Chengwei Fan

“…Active subspace was used to compute the active variables via singular value decomposition and a hybrid polynomial correlated function expansion was used to construct a surrogate model on the active subspace. …”
Get full text

High-accuracy solution of pantograph differential equations subject to mixed boundary conditions via shifted Vieta–Lucas polynomials by R. M. Hafez, H. M. Ahmed

“…A Galerkin method (GM) is formulated for constant coefficient-type equations, and a spectral collocation method (SCM) is given for variable coefficient cases. …”
Get full text

Relación entre comunidad íctica y cobertura vegetal riparia en dos períodos hidrológicos (Eje Cafetero, Colombia) by María Angélica Pérez-Mayorga, Saúl Prada-Pedreros

“…Therewere no significant differences (P>0.05) among the structural variables, the HYPE and the RVC. According to r and r2 the diet of most fish species did not vary as a function of RVC and HYPE; however, according to the CCA diet varies as a function of HYPE but not of RVC. …”
Get full text

Extension of the First-Order Recursive Filters Method to Non-Linear Second-Kind Volterra Integral Equations by Rodolphe Heyd

“…In addition, this new approach extends for the first time the field of use of first-order recursive filters, usually restricted to the case of linear ordinary differential equations (ODEs) with constant coefficients, to the case of non-linear ODEs with variable coefficients. …”
Get full text

Evaluation of Face Stability for Mega Tunnel Under Varying Ground Strength Parameters by Deshpande Shilpa, Hedaoo Namdeo

“…This study investigates the impact of various geological strength variables, such as Young’s modulus and coefficient of lateral earth pressure, on Mega Tunnel face stability. …”
Get full text

Sinc-Chebyshev Collocation Method for a Class of Fractional Diffusion-Wave Equations by Zhi Mao, Aiguo Xiao, Zuguo Yu, Long Shi

“…This paper is devoted to investigating the numerical solution for a class of fractional diffusion-wave equations with a variable coefficient where the fractional derivatives are described in the Caputo sense. …”
Get full text

Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran by Seyed Hossein Mirmosavi, kohzad Raispour, Muhammad Kamangar

“…Conclusion The results of this study with respect to the correlation coefficient of 0.5012 with real data and high spatial resolution of the output map showed the efficiency of using different bands of radar images in estimating surface moisture. …”
Get full text

Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…In recent years, the use of machine learning techniques (ML) has become widespread for analysing the effects of operational factors on anaerobic digestion efficiency. Among these, Support Vector Regression (SVR) with a Radial Basis Function (RBF) kernel has been used to predict biogas yield based on diverse operating parameters. …”
Get full text

Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Confusion matrix analysis further confirmed RF as the optimal model, achieving 0.875 accuracy and robust inter-rater agreement (Cohen's kappa coefficient = 0.696) in the testing cohort. SHAP analysis identified the adenoid-to-nasopharyngeal ratio as the predominant diagnostic indicator, followed by tympanometric type and history of recurrent respiratory infections.ConclusionAn RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.…”
Get full text

INVESTIGATION OF UV/TiO2-ZnO-Co PHOTOCATALITIC DEGRADATION OF AZO DYE (REACTIVE RED 120) BY RESPONSE SURFACE METHODOLOGY by MOHSEN MANSOURI, MARJAN TANZIFI, HOSSEIN LOTFI, MOHSEN NADEMI

“…Results were in agreement with empirical values and the sensitivity analysis showed above parameters as the most efficient variables in decolorization efficiency. Analysis of variance (ANOVA) revealed highly determination coefficient value (R2 = 0.9996 and adjusted-R2 = 0.999) and satisfactory prediction second-order regression model. …”
Get full text

Online identification of stability region for large-scale wind farms, Part I: Clustering based piecewise affine impedance modeling by Jia Luo, Peng Wang, Haoran Zhao, Chenxinwei Yuan, Tiancheng Liu, Vladimir Terzija

“…In each partition, the impedance is expressed as a first-order explicit function of the complex variable and the operating state variables. …”
Get full text

On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

“…The nonlinear differential equations were studied using an original, explicit, and very efficient technique, namely the optimal auxiliary functions method (OAFM). …”
Get full text

Impact of changes in land use in the flow of the Pará River Basin, MG by Evandro L. Rodrigues, Marcos A. T. Elmiro, Francisco de A. Braga, Claudia M. Jacobi, Rafael D. Rossi

“…The adjusted model was assessed by the coefficient of efficiency of Nash-Sutcliffe (between -0.057 to -0.059), indicating high correlation and coefficient of residual mass (0.757 to 0.793) and therefore a satisfactory fit. …”
Get full text

Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
Get full text

Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
Get full text

Nonlinearity Estimation and Compensation for Accurate PMSM Modeling and Voltage Prediction by Beichen Ding, Yuting Lu, Chunyan Lai, Weiwen Peng, Kaide Huang, Guodong Feng

“…Specifically, the offsets to the base model are modeled using nonlinear functions with variable coefficients to compensate saturation and core loss effect, which can achieve better accuracy without changing the model structure. …”
Get full text

The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
Get full text

Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

“…The diffusion coefficient extracted from the moisture ratio function was used to assess the drying kinetics, while SEC was used to evaluate the energy efficiency of the EHD dehydrator under different parameter settings. …”
Get full text