Stochastic Analysis of Nonlinear Vehicle-Track Coupled Dynamic System and Its Application in Vehicle Operation Safety Evaluation by Fu-Shan Liu, Zhi-Ping Zeng, Wei-Dong Wang, Abdulmumin Ahmed Shuaibu

“…The nonlinear coupled vehicle-track dynamic system is used to accurately describe the wheel-rail contact state. The stochastic function-spectral representation is used to simulate the random track irregularity in the time domain for the first time; consequently, the frequency components in the irregularity are preserved and random variables are reduced. …”
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Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach by Alireza Naeini, Alireza Jalali, Ehsan Houshfar

“…A neural network model is utilized to predict how the objective functions vary with six decision variables. The chosen optimization approach utilizes the genetic algorithm (GA) method. …”
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Application of a novel metaheuristic algorithm inspired by connected banking system in truss size and layout optimum design problems and optimization problems by Mehrdad Nemati, Yousef Zandi, Jamshid Sabouri

“…Besides the truss size/layout problems, CEC-BC-2017 test functions with ten dimensions and also three other constrained optimum design problems are also investigated to examine the performance of the CBSO in dealing with these standard unconstrained and constrained test functions. …”
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Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

“…BBO has demonstrated good performance on various unconstrained and constrained benchmark functions. It has also been applied to real world optimization problems of type linear or nonlinear, nominal or ordinal as well as mixed variables. …”
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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. …”
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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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Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

“…Taking these process parameters (<italic>x</italic>, <italic>y</italic>, <italic>z</italic>, <italic>d</italic>, <italic>h</italic>, <italic>n</italic>, <italic>a</italic>_p, <italic>a</italic>_e, <italic>f</italic>_z) as design variables, a multi-objective optimization model is constructed to balance machining efficiency and tool life. …”
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Predicting the Probability of Failure in Truss Structures Using Artificial Neural Networks by Mohammadreza Gholami, Seyed Ahmad Mobinipour, Mohammad Javad Haji Mazdarani, Seyed Rohollah Hoseini Vaez

“…The limitation of node displacement is considered as a limit state function. The data was split as 60% for training and 40% was used for testing and validation. …”
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Cardio-Ankle Vascular Index and Indices of Diabetic Polyneuropathy in Patients with Type 2 Diabetes by Akihiko Ando, Michiaki Miyamoto, Kazuhiko Kotani, Kenta Okada, Shoichiro Nagasaka, Shun Ishibashi

“…The cardio-ankle vascular index (CAVI) is used to test vascular function and is an arterial stiffness marker and potential predictor of cardiovascular events. …”
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Adaptive Fault-Tolerant Control of Mobile Robots with Fractional-Order Exponential Super-Twisting Sliding Mode by Hao Wu, Shuting Wang, Yuanlong Xie, Hu Li

“…To address the time-varying LIP faults and uncertainties, a novel barrier function (BF)-based gain is explored to assist the super-twisting law. …”
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Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits. by Mohsen Yoosefzadeh-Najafabadi, Dan Tulpan, Milad Eskandari

“…Yield is a complex trait and reliant on various related variables called yield components. In this study, the five most important yield component traits in soybean were measured using a panel of 250 genotypes grown in four environments. …”
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Performance Analysis of Reconfigurable Intelligent Surface-Assisted Underwater Wireless Optical Communication Systems by Qi Zhang, Dian-Wu Yue, Xian-Ying Xu

“…In the RIS-assisted UWOC systems with intensity modulation and direct detection (IM-DD), we apply the approximate distribution of the sum of Gamma-Gamma random variables to derive the probability density function (PDF) of the instantaneous received signal-to-noise ratio (SNR) for the first time. …”
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An Investigation of Knee Injury Prevalence and its Mechanism among Premier League Soccer Referees in Iran by Hamid Mahdavi Mohtasham, Shahnaz Shahrbanian

“…Using the Pearson correlation coefficient, this study examined the relationships between different variables including KOS subscales as well as the current level of self-reported knee joint function and proprioception. …”
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Analysis of Mobile JKN Application Service Quality With E-GovQual Method and IPA by Randy Rizki Ananda, Indriani Noor Hapsari

“…The results of the coefficient of determination (R-Square) show that overall, the variables of ease of use, reliability, trust, content and appearance, functionality and interaction and citizen support significantly affect service quality by 88.6%. …”
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A Hybrid Model for Carbon Price Forecasting Based on Secondary Decomposition and Weight Optimization by Yongfa Chen, Yingjie Zhu, Jie Wang, Meng Li

“…Secondly, a two-stage feature-selection method is employed, in which the partial autocorrelation function (PACF) is used to select relevant lagged features, while the maximal information coefficient (MIC) is applied to identify key variables from both historical and external data. …”
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Donor Parameters and Platelet Yield during Plateletpheresis: A Cross-sectional Prospective Study by Ruchi Singh, Ganga S. Pilli, Ramadevi Vivek Wani

“…A relationship between pre-donation donor variables and platelet yield was studied using the Pearson correlation coefficient (r). …”
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Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

“…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
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Rational and Irrational Investor Sentiments and Stock Market Returns: Evidence from the Tehran Stock Exchange by Mohammad Nadiri, Hamid Reza Panahian

“…In the first step, we used an autoregressive distributed lag (ARDL) technique to regress macroeconomic fundamental variables on individual and institutional investor sentiments to decompose the sentiment variables into rational and irrational components. …”
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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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