Development of data-driven machine learning models and their potential role in predicting dengue outbreak by Bushra Mazhar, Nazish Mazhar Ali, Farkhanda Manzoor, Muhammad Kamran Khan, Muhammad Nasir, Muhammad Ramzan

“…This involves gathering data on various climatic factors, including temperature, rainfall, relative humidity, and wind speed, along with monthly records of dengue cases. The study functions as an efficient warning system, enabling the anticipation of dengue outbreaks. …”
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Two Weighted Fuzzy Goal Programming Methods to Solve Multiobjective Goal Programming Problem by Mousumi Gupta, Debasish Bhattacharjee

“…Here, the relative weights represent the relative importance of the objective functions. The proposed methods involve one additional goal constraint by introducing only underdeviation variables to the fuzzy operator λ (resp., 1-λ), which is more efficient than some well-known existing methods such as those proposed by Zimmermann, Hannan, Tiwari, and Mohamed. …”
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Analysis of Mechanical and Thermal Material Characteristics of GPL-Reinforced Double-FG Composite Nanoplates under Temperature Load by Kerim Gökhan Aktaş

“…The analysis is conducted to evaluate the influence of variables like temperature rise, GPLs weight ratio and GPLs distribution patterns on the thermal and mechanical properties of the nanoplate such as effective modulus of elasticity, Poisson's ratio, coefficient of thermal expansion and coefficient of thermal conductivity. …”
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A Particle Swarm Optimization-Guided Ivy Algorithm for Global Optimization Problems by Kaifan Zhang, Fujiang Yuan, Yang Jiang, Zebing Mao, Zihao Zuo, Yanhong Peng

“…In recent years, metaheuristic algorithms have garnered significant attention for their efficiency in solving complex optimization problems. …”
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Utilizing a Transient Electromagnetic Inversion Method with Lateral Constraints in the Goaf of Xiaolong Coal Mine, Xinjiang by Yingying Zhang, Bin Xie, Xinyu Wu

“…Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. …”
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Dynamic Surrogate Optimization of Vertically Stacked Nanosheet FET Based on Gaussian Process Regression by Christofer N. Yalung, Doldet Tantraviwat

“…Source extension (<inline-formula> <tex-math notation="LaTeX">$S_{ext}$ </tex-math></inline-formula>), drain extension (<inline-formula> <tex-math notation="LaTeX">$D_{ex\mathrm {t}}$ </tex-math></inline-formula>), gate length (<inline-formula> <tex-math notation="LaTeX">$L_{g}$ </tex-math></inline-formula>), nanosheet height (NSh), nanosheet width (NSw), and number of fin (nfin) make up the input variables. In addition to applying normalization to make the weight assignment to the goal functions easier, a penalty component was incorporated to manage the <inline-formula> <tex-math notation="LaTeX">$V_{T}$ </tex-math></inline-formula>. …”
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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

“…The Pearson correlation coefficient between the original OCO-2 SIF data and MODIS GPP stood were at a modest 0.53. …”
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An Effective AFNIS-MPPT-Based Method for Optimizing Hybrid Energy Harvesting Systems by Muhammad Saqib, Ghulam Sarwar Kaloi, Mehr Gul, Muhammad Shahzad Nazir, Mohsin Ali Koondhar, Lutfi Albasha, Faisal Alsaif

“…The increasing global demand for renewable energy, particularly from solar and wind sources, highlights the need for sophisticated control strategies to optimize power generation efficiency. Maximum Power Point Tracking (MPPT) techniques are essential for improving the performance of Hybrid Renewable Energy Systems by maximizing power extraction from variable sources. …”
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Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…The improved model comprises four functional components. The innovation of this study lies in several aspects. …”
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Digital Twin Control Method of Machine Tool Feed Rate Based on Fuzzy Neural Network by YIN Jia, BAI Lele, TIAN Hui, WU Shijie, Hou Guijin, TANG Yuyang, LIU Hongguang, ZHANG Jun

“…The fuzzy neural network is trained based on the machining data, and the corresponding fuzzy control rules and membership functions are obtained. The control rules are modified according to the actual machining conditions. …”
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Evaluation of the Wind-Resistant Performance of Long-Span Cable-Stayed Bridge Using the Monitoring Correlation between the Static Cross Wind and Its Displacement Response by Gaoxin Wang, Youliang Ding, Dongming Feng, Jihong Ye

“…Third, considering that the traditional function cannot match the monitoring correlation very well, some new fitting functions are thoroughly studied to determine the best function for fitting the monitoring correlation. …”
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A Comparative Study of Deep Reinforcement Learning Algorithms for Urban Autonomous Driving: Addressing the Geographic and Regulatory Challenges in CARLA by Yechan Park, Woomin Jun, Sungjin Lee

“…To evaluate the adaptability of each algorithm to geographical variability and complex traffic laws, scenario-specific reward and penalty functions were carefully designed and incorporated. …”
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Active Disturbance Rejection Control for an automotive suspension system based on parameter tuning using a fuzzy technique. by Tuan Anh Nguyen

“…The proposed method is formed based on the combination of an Active Disturbance Rejection Control (ADRC) technique with control coefficients tuned by a dynamic fuzzy technique formed based on special membership functions called Active Disturbance Rejection Control Based on Fuzzy (ADRCBF). …”
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Research and Development Expenditures and Economic Growth in the EU: A Panel Data Analysis by Freimane Rita, Bāliņa Signe

“…The estimated model is the production function type standard growth model extended with R&D stock variable. …”
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Fault Estimation for Semi-Markov Jump Neural Networks Based on the Extended State Method by Lihong Rong, Yuexin Pan, Zhimin Tong

“…To alleviate network congestion and optimize communication resources, the Round-Robin protocol is adopted to schedule data transmission efficiently. By constructing a Lyapunov–Krasovskii functional and applying the discrete Wirtinger inequality, sufficient conditions are derived to ensure the mean square exponential stability and dissipative performance of the system. …”
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Agricultural Waste–Derived Biochar for Antibiotics Removal in Aqueous Environment: A Comprehensive Outlook by Varalakshmi Varatharajan, Karthik V., Selvakumar Periyasamy

“…The key elements influencing antibiotic adsorption on biochar, including surface chemistry, pyrolysis conditions, and environmental variables, were discussed in detail. This review focuses specifically on the functional modification of the biochar, the mechanism involved in antibiotic adsorption, and the scalability of this process. …”
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On practical aspects of optimal modelling in boundary element method by A. Brański, R. Olszewski

“…Since the optimal discretization theory derived for the function of one variable, then only the 2D problem is considered. …”
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Similarity Solutions for Multiterm Time-Fractional Diffusion Equation by A. Elsaid, M. S. Abdel Latif, M. Maneea

“…Based on the obtained results, we propose a definition for a multiterm error function with generalized coefficients.…”
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Economic and environmental power dispatch for energy management systems applied to microgrids with wind energy resources and battery energy storage systems by Jhon Montano, John E. Candelo-Becerra, Cristian Escudero-Quintero, Juan Pablo Guzmán

“…The results show that the approach ensures technical efficiency while minimizing economic and environmental requirements. …”
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Coherence of brain electrical activity: a quality of life indicator in Alzheimer’s disease?Coerência da atividade elétrica cerebral: indicador da qualidade de vida na doença de Alz... by Lineu Corrêa Fonseca, Gloria M. A. S. Tedrus, Ana Laura R. A. Rezende, Heitor F. Giordano

“…Conclusion Interhemispheric coherence correlates with QOL regardless of cognitive and functional variables and seems to be a neurophysiological indicator of QOL in AD patients.…”
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