Optimizing switching sequences in AC-AC converters for enhanced safety and performance in conveyor systems by Velmurugan Dhandapani, Gopinath Balasubramanian

“…Industrial systems require optimized control to maintain efficiency under variable loads. Fault conditions influence power stability and overall system functionality. …”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.…”
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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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An Optimal Hybrid Control Method for Energy-Saving of Chilled Water System in Central Air Conditioning by Yan Zhang, Xiaoli Chu, Yongqiang Liu

“…Here, an optimum control method is proposed with the principle of the minimum, by setting the minimum power consumption as the performance function in fixed time, which realizes variable control of pumps and accurate adjustment of temperature inside room. …”
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Jacobian-Free Newton Krylov Methods for Steady and Transient Neutron Transport Models by ZHANG Yangyi, ZHANG Tiancheng, ZHOU Xiafeng

“…To further improve computational efficiency of comeSn_JFNK, in the JFNK solution, neutron scalar fluxes instead of neutron angular fluxes were chosen as the global solution variables. …”

Transfer Robustness Optimization for Urban Rail Transit Timetables by Liqiao Ning, Peng Zhao, Wenkai Xu, Ke Qiao

“…Next, to improve the computational efficiency, we propose an approximate linearization approach for the EETC function and introduce two types of binary variables and auxiliary substitution variables to convert the nonlinear model to a mixed-integer linear model. …”
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A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

“…The study employed the batch collection of training samples utilizing experience replay and a double-network mechanism, along with the preprocessing of neural network state inputs, and the investigation into feasible regions within the action space using a variable ε-greedy strategy. A loss function based on the value function was then constructed, and network parameters were updated iteratively by a batch gradient descent method. …”
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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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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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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. …”
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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. …”
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COMPARATIVE ANALYSIS OF THE ACADEMIC PERFORMANCE IN THE AGRICULTURAL UNIVERSITIES FROM ROMANIA AND REPUBLIC OF MOLDOVA USING THE NONPARAMETRIC METHOD OF DATA ENVELOPMENT ANALYSIS by Ilie CERCEL, Gina FÎNTÎNERU, Elena TOMA, Augustin VOLCONOVICI, Alla CHIRSANOVA, Anatol RACUL

“…As a result of analyzing the academic performance rating by option variable returns to scale, it is possible to determine the resources for improving staff activity by evaluating the distance function for each causal factor.…”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Optimal Control Problem of Converter Steelmaking Production Process Based on Operation Optimization Method by Jun Zhang

“…The optimal control indicator is determined via current state of converter smelting production process, and the set values of operation variable would control converter production. Relationship between various operating variables, current temperature, and carbon content is constructed through operation analysis of a great deal of actual production data; then, the dynamic optimal control indicator is derived from historical excellent smelting data; finally, the dynamic operation optimization model is built by taking the minimum deviation between the current data—molten steel temperature and carbon content—and optimal data which are determined by the optimal control indicator as objective function. …”
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Estimation of micro-extraction process hippuric acid for toluene exposure monitoring in urine samples by Behnaz Sarani, Mashaallah Rahmani, Ahmad Reza Abbasian

“…Abstract This study employed a quick, efficient, sensitive, and easy-to-use micro-extraction process to monitor biomarker hippuric acid (BIHA) in urine samples as a bioindicator of exposure to toluene with an HPLC-DAD instrument. …”
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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. …”
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Mitigating Load Imbalance and Enhancing Distribution Transformer Performance via Fuzzy Inference System by Althoff Hibban, Azriyenni Azhari Zakri, Dirman Hanafi, Boy Ihsan, Umair Ali

“…To address this issue, this study proposes a fuzzy logic-based approach using a Mamdani-type Fuzzy Inference System (FIS). The input variables, current magnitudes in phases R, S, and T, are represented by trapezoidal membership functions classified into several categories. …”
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Estimation of Total Suspended Solids Concentration in Streams Using Regression and Artificial Neural Networks Methods by Betül Mete, Sinan Nacar, Adem Bayram, Osman Tuğrul Bak

“…Root mean square error, mean absolute error, and Nash-Sutcliffe (NS) efficiency coefficient statistics were used to evaluate the model and method performances. …”
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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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Trajectory Planning Method in Time-Variant Wind Considering Heterogeneity of Segment Flight Time Distribution by Man Xu, Jian Wang, Qiuqi Wu

“…This study aims to optimize a reliable and efficient trajectory by minimizing the Mean-Excess Flight Time (MEFT). …”
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