Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

Subjects: “…Parameter estimation…”
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Medium- and Long-term Runoff Prediction Based on SMA-LSSVM by TIAN Jinghuan, LI Congxin, LI Ang

Subjects: “…least squares support vector machine (LSSVM)…”
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A forestry investigation: Exploring factors behind improved tree species classification using bark images by Gokul Kottilapurath Surendran, Deekshitha, Martin Lukac, Martin Lukac, Jozef Vybostok, Martin Mokros

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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

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Classification of Fritillaria thunbergii appearance quality based on machine vision and machine learning technology by DONG Chengye, LI Dongfang, FENG Huaiqu, LONG Sifang, XI Te, ZHOU Qin’an, WANG Jun

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Performance evaluation of geopolymer masonry units: A hybrid approach combining laboratory testing and AI modeling by Md. Zia Ul Haq, Sandeep Singh, Tarak Vora, A.K. Dasarathy, Kaushik Bharti, Vanitha S, Priyadarshi Das, Laura Ricciotti

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Predicting the diabetic foot in the population of type 2 diabetes mellitus from tongue images and clinical information using multi-modal deep learning by Zhikui Tian, Dongjun Wang, Xuan Sun, Chuan Cui, Hongwu Wang

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Effect of plateletpheresis on donor variables and platelet yield using three different cell separators: Experience from tertiary care hospital by Sarita Sharma, Sunita Bundas, Nippun Prinja, Amit Sharma, Rachna Narain

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Optimization of process parameters in 3D-nanomaterials printing for enhanced uniformity, quality, and dimensional precision using physics-guided artificial neural network by Anita Ghandehari, Jorge A. Tavares-Negrete, Jerome Rajendran, Qian Yi, Rahim Esfandyarpour

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Factors Associated with COVID-19 Mortality in Mexico: A Machine Learning Approach Using Clinical, Socioeconomic, and Environmental Data by Lorena Díaz-González, Yael Sharim Toribio-Colin, Julio César Pérez-Sansalvador, Noureddine Lakouari

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Performance evaluation and multi-objective optimization of EDM parameters for Ti6Al4V using different tool electrodes by Manoj Jagdale, Masuk Abdullah, Nitin Ambhore, Atul Kulkarni, Rakesh Chaudhari, Jay Vora, József Menyhárt

“…Abstract Ti6Al4V alloy is widely used in aerospace and biomedical applications due to its excellent mechanical and thermal properties, but its poor machinability makes it a difficult-to-cut material. Electrical Discharge Machining (EDM) offers an effective non-conventional machining approach for such materials, where tool electrode selection and process parameters critically influence performance. …”
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Blade optimal design parameters determination by N. T. Surashov, R. B. Asmatulaev, D. N. Tolymbek

“…In Kazakhstan in present time there is a large number of earthmoving works, which leads to an increase in the demand for earthmoving-transport machines (ETM), in particular bulldozers of different types. …”
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Neural networks for parameter estimation in geostatistical models with geometric anisotropies by Alejandro Villazón, Alfredo Alegría, Xavier Emery

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Parameter uncertainties for imperfect surrogate models in the low-noise regime by Thomas D Swinburne, Danny Perez

“…The approach is demonstrated on model problems before application to thousand-dimensional datasets in atomistic machine learning. Our efficient misspecification-aware scheme gives accurate prediction and bounding of test errors in terms of parameter uncertainties, allowing this important source of uncertainty to be incorporated in multi-scale computational workflows.…”
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Parameter Matching of Battery–Supercapacitor Hybrid Power System for Electric Loader by Mingkun Yang, Gexin Chen, Chao Ai, Xianhang Liu, Tao Jiang

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Statistical and Machine Learning Classification Approaches to Predicting and Controlling Peak Temperatures During Friction Stir Welding (FSW) of Al-6061-T6 Alloys by Assad Anis, Muhammad Shakaib, Muhammad Sohail Hanif

“…This research work employed a novel approach by investigating the effect of FSW welding process parameters on peak temperatures through the implementation of finite element analysis (FEA), the Taguchi method, analysis of variance (ANOVA), and machine learning (ML) algorithms. …”
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Effects of EDM parameters on residual stress and microhardness in Al-10 %SiCmicro-SiCnano hybrid composites: A Simulation and Experimental study by Umair Arif, Imtiaz ali Khan, Faisal Hasan, Afsar Husain, Sanan H. Khan

“…The simulations indicated the formation of compressive residual stresses in the hybrid composites in machined area and tensile residual stresses away from it.. …”
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Inversion of Water Quality Parameters from UAV Hyperspectral Data Based on Intelligent Algorithm Optimized Backpropagation Neural Networks of a Small Rural River by Manqi Wang, Caili Zhou, Jiaqi Shi, Fei Lin, Yucheng Li, Yimin Hu, Xuesheng Zhang

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On the machinability threshold of dynamic lithography by Yang He, Liangchi Zhang

“…The findings by this study provide valuable insights into the intricate relationship between nano-machining parameters and machinability thresholds within the realm of dynamic lithography, offering practical implications for applications in the field.…”
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VIBRATION SIMULATION OF TECHNOLOGICAL MACHINE BODY IN THE DYNAMIC BRAKING MODE OF ASYNCHRONOUS MACHINE WITH FREQUENCY CONTROL by Nikolay F. KARNAUKHOV, Julia V. PUDOVA, Maxim N. FILIMONOV

“…Simulation of the vibration level of technological machines (TM) with an asynchronous electric frequency control allows to detect causes of interference effects, to identify oscillation suppression technics. …”
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