Enhanced Stability and Control of Solar Powered EV Charging Stations Using Disturbance Observer-Based Adaptive Sliding Mode Control for DC Voltage Stabilization by Surabhi Bagherwal, Subhasish Mahapatra

“…To address the chattering issue, a barrier function based SMC (BFSMC) approach is proposed. The distinctive aspects of this BFSM control approach is its capability to stabilize the designed sliding variable to a predefined neighbourhood around the origin within a limited duration, eliminating the need for prior understanding of the maximum limit of the lumped disturbance. …”
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Development and validation of a novel prediction model for osteoporosis: from serotonin to fat-soluble vitamins by Jinpeng Wang, Lianfeng Shan, Jing Hang, Hongyang Li, Yan Meng, Wenhai Cao, Chunjian Gu, Jinna Dai, Lin Tao

“…Stepwise discriminant analysis was performed to identify efficient predictors for osteoporosis. The prediction model was developed based on Bayes and Fisher’s discriminant functions, and validated via leave-one-out cross-validation. …”
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Coordination of technology of railway operation of the Republic of Tajikistan and organization of railways in international traffic by P. N. Pulatov

“…Proposed classification of technological restrictions and controlled variables in the performance of transport takes into account methods for changing external conditions for the functioning of the railway landfill and methods for increasing internal efficiency of its operation. …”
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ABOUT SOME FEATURES OF TRANSMISSION MODE FOR ACTIVE POWER OF ELECTRICAL LINE by Paţiuc V., Berzan V.P., Anisimov V., Cabac S., Postotonca S.

“…It enteritis that for the active character load of the active power input and power output of the line, so functions , and functions that characterize developments efficiency , power factor at the input line and the load power factor when the variable z. …”
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Faktor-Faktor Yang Mempengaruhi Pertumbuhan Ekonomi Di Jawa Timur Dengan Pendekatan Spatial Regression by Rendra Erdkhadifa

“…The research results show that the weighting function used is fixed gaussian, and the spatial model has a coefficient of determination of 92.97%. …”
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Lattice Boltzmann Method for the Generalized Black-Scholes Equation by Fangfang Wu, Duoduo Xu, Ming Tian, Yingying Wang

“…The proposed lattice Boltzmann model can also be applied to a class of partial differential equations with variable coefficients and source terms.…”
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Enhancing epidemic preparedness: a data-driven system for managing respiratory infections by Moslem Sarani, Katayoun Jahangiri, Manoochehr Karami, Mohammadreza Honarvar

“…Results Key data categories include individual-level variables, such as age, symptoms, and vaccination records, alongside population-level metrics like infection rates and regional vaccination coverage enabling functionalities such as identifying high-risk individuals, tracking infection dynamics, and optimizing resource allocation. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…To this end, the feature importance analysis of MSW input variables was carried out using the decision tree regressor with the Gini importance (GI) metrics to identify the most influential variable. …”
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Prediction of suicidal attempts among Chinese adolescents with mood disorders: a clinical study using a machine learning approach by Jianbing Li, Yinqiu Zhao, Chi Yang, Wenqing Li, Zhihao Huang, Changhe Fan

“…However, there is a need for studies of accurate and efficient SA models specifically for use in adolescents with mood disorders due to a lack of existing research integrating risk variables when predicting clinical SA. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…Statistical metrics confirmed that the proposed OMVMD-GRKR model, concerning the best efficiency in the Ahvaz (R = 0.987, RMSE = 0.761, and U95% = 2.108) and Molasani (R = 0.963, RMSE = 1.379, and U95% = 3.828) stations, outperformed the OMVMD and simple-based methods such as ridge regression (Ridge), least squares support vector machine (LSSVM), deep random vector functional link (DRVFL), and deep extreme learning machine (DELM). …”
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Regression analysis and artificial neural networks for predicting pine species volume in community forests by Wenceslao Santiago-García

“…The regression approach employed seemingly unrelated nonlinear regression (NSUR) to fit simultaneous additive volume systems using both one- and two-variable models. In this approach, volume was modeled as a function of diameter at breast height (d) alone and as a function of both d and total tree height (h). …”
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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. …”
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Empirical Study of the Impact of Unemployment on Political Stability in Iran (1985-2015) by habib samani, robabeh khilkordi

“…Vector regression (VAR), Johansson-Juselius, Vector Error Correction Model (VECM), and variance analysis function were used for this purpose. The results show that in the long run, two variables of unemployment rate and Gini coefficient have a negative and significant relationship with political stability. …”
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Testing the Level of Alternative Institutions as a Slowdown Factor of Economic Development: the Case of Montenegro by Mimo Draškovic, Sanja Bauk, Dalia Streimikiene, Veselin Draskovic

“…On the basis of the conducted statistical examines: standard error of the regression estimate, correlation coefficient, and coefficient of determination are calculated on the basis of previously determined regression coefficients and forecast values of the linear function of free variables (factors: a, b, and c). …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…Therefore, Na+, Cl+, Na%, CO3 −, and SO4 2− were used as input variables (independent variables), and EC, TDS, and SAR were used as output variables (dependent variables). …”
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Factors Influencing Telemedicine Adoption Among Health Care Professionals: Qualitative Interview Study by Fiona Schürmann, Daniel Westmattelmann, Gerhard Schewe

“…Perceived benefits encompassed convenience through reduced travel time (5/14, 36%), improved care quality due to higher accessibility (8/14, 57%), and operational efficiency (7/14, 50%). Trust referents played a pivotal role; trust in technology was linked to functionality (6/14, 43%) and reliability (5/14, 36%), while trust in treatment depended on effective collaboration (9/14, 64%). …”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…By integrating AI techniques, such as back propagation neural networks, the framework predicts variables with high computational complexity, improving accuracy and simulation efficiency. …”
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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…To efficiently analyze and optimize the structural performance of rudder structures, a parametric optimization model for the radial configuration of reinforcement ribs is constructed. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems by Amirhossein Hamzeiyan, Armin Ebrahimi

“…Peak shaving with energy storage systems (ESSs) is a promising approach to optimize energy use, reduce costs, and ensure a more reliable power grid.This paper aims to improve the performance of a novel control algorithm for efficient peak shaving by using sensitivity analysis and multi-objective optimization techniques. …”
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