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. …”
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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. …”
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A Study of Some Properties of Fuzzy Laplace Transform with Their Applications in Solving the Second-Order Fuzzy Linear Partial Differential Equations by Elhassan Eljaoui, Said Melliani

“…Then, some properties dealing with the partial derivatives of fuzzy Laplace transform for a fuzzy function of two real variables have been proved. Afterwards, an algorithm of fuzzy Laplace transform for solving second-order fuzzy partial differential equations has been proposed. …”
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Vibration Analysis of Rotating Tapered Timoshenko Beams by a New Finite Element Model by Bulent Yardimoglu

“…A new finite element model is developed and subsequently used for transverse vibrations of tapered Timoshenko beams with rectangular cross-section. The displacement functions of the finite element are derived from the coupled displacement field (the polynomial coefficients of transverse displacement and cross-sectional rotation are coupled through consideration of the differential equations of equilibrium) approach by considering the tapering functions of breadth and depth of the beam. …”
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Providing a Robust Dynamic Pricing Model and Comparing It with Static Pricing in Multi-level Supply Chains Using a Game Theory Approach by Sara Mehrjoo, Hanan Amoozad Mahdirji, Jalil Heidary Dahoei, Seyyed Hossein Razavi Haji Agha, Mahnaz Hosseinzadeh

“…Initially, the model introduces symbols: x as the vector of design variables, and y as the vector of control variables. …”
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An evolutionary-based optimization algorithm for truss sizing design by Pham Hoang Anh

“…Here, the constraints and objective function are treated separately so that both function and constraint evaluations can be saved. …”
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Peroral endoscopic myotomy for complex achalasia and the POEM difficulty score: An update by Carmen Ching Hui Yee, Michael Youssef, Matthew Woo, Robert Bechara

“…PDS correlates moderately with procedural efficiency with a correlation coefficient of 0.595 (Spearman's p < 0.001). …”
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The Impact of Land Circulation on Common Prosperity in the Digital Economy Context by Cong Xu, Feng Wu, Jingran Lin, Yie-Ru Chiu

“…It finds that land circulation is consistent with the theory of the siphoning effect. DE (DE) variables accelerate the circulation of information factors and improve the allocative efficiency of land, technology, and capital factors. …”
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带传动软启动装置蜗杆的优化设计 by 赵江平

“…By the mechanical analysis of the belt drives soft-start equipment,tow-objective function is established with the worm axial modulus and spiral angle as the independent variables.Based on self-locking constraint and fuzzy constraint conditions,constraint subset is established.Compared with the general design parameters,the rustle shows that the spiral angle is increased and the worm axial modulus is decreased.The test shows that the optimize design effectively improve the transmission efficiency,and reduce the minimum power of the speed adjustment motor.…”
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Numerical solutions for fractional optimal control problems using Mü‎‎‎‎‎‎‎ntz-Legendre polynomials by Mohammad Sahabi, Allahbakhsh Yazdani Cherati

“…To achieve this, stable and efficient methods for calculating the fractional integral and derivative operators of Müntz-Legendre functions based on three-term recurrence formulas and Jacobi-Gauss quadrature rules are presented. …”
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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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A New Noninterior Continuation Method for Solving a System of Equalities and Inequalities by Jianguang Zhu, Binbin Hao

“…By using slack variables and minimum function, we first reformulate the system of equalities and inequalities as a system of nonsmooth equations, and, using smoothing technique, we construct the smooth operator. …”
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Research on Constraint Processing Method of High-dimensional Optimization Operation Problem of Cascade Reservoirs by Zhongzheng HE, Shuliang LI, Wei HUANG, Feng YAN, Jisi FU, bin XIONG

“…The intelligent optimization algorithm is a multidimensional linkage random search, which boasts a vast optimization space but suffers from low optimization efficiency. Therefore, this study introduces a constraint processing approach that integrates a penalty function with nested DPSA–POA and intelligent algorithms and applies it to the optimal flood control operation problem of cascade reservoirs in the middle reaches of the Ganjiang River, with decision variables extending to 2196 dimensions. …”
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A design-based framework for optimal stratification using super-population models with application on real data set of breast cancer. by Faizan Danish

“…This study investigates the determination of stratification points for two study variables within the framework of simple random sampling, with a focus on estimating the population mean using a closely related auxiliary variable. …”
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Optimum Design of RC Beams Strengthened with Externally Bonded FRP Using Pattern Search by Noor Mohammed Sheet, Baraa J. M. AL-Eliwi, Rabi M. Najem

“…The design process involved an objective function that represents the cost function of the optimum solution and design variables that define the optimum dimensions of the beam and FRP material, such as beam width, effective beam depth, FRP strip thickness, FRP strips spacing, and FRP strip width, according to the design constraints of the ACI 440-2R-17 code. …”
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Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor by Jun Yang, Xian-yu Wu, Zhen-guo Wang

“…The fuel equivalence ratio for each injection port was taken as the design variables. And the combustion efficiency, the total pressure recovery coefficient, and the drag coefficient were chosen as the objective functions. …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. …”
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Fuzzy Controller Design Optimized by the Grasshopper Algorithm to Realize Maximum Power in Photovoltaic Systems by Kamran Safaei, Aida Esmaeilian-Marnani, Hossein Emami, Amir Hossein Zaeri

“…In this paper, the ISE evaluation index is employed as the cost function of algorithm to verify the obtained results. …”
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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. …”
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Kernel Density Estimation for Joint Scrambling in Sensitive Surveys by Alvan Caleb Arulandu, Sat Gupta

“…Randomized response models aim to protect respondent privacy when sampling sensitive variables but consequently compromise estimator efficiency. …”
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