Multi-Objective Automated Machine Learning for Inversion of Mesoscopic Parameters in Discrete Element Contact Models by Xu Ao, Shengpeng Hao, Yuyu Zhang, Wenyu Xu

Subjects: “…mesoscopic parameter inversion…”
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Monitoring water quality parameters using multi-source data-driven machine learning models by Yubo Zhao, Mo Chen, Jinyu He, Yanping Ma

“…This study integrated field data, multispectral imagery, meteorological data, and hydrological data to invert the water quality conditions of aquatic environments. A machine learning model (CNN-RF) was developed to estimate three water quality parameters (TP, DO, COD), and its performance was comprehensively evaluated using four error indices (R², MAE, MSE, MAPE). …”
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Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO by Yunxiang Chen, Jie Bao, Rongyao Chen, Bing Li, Yuan Yang, Lupita Renteria, Dillman Delgado, Brieanne Forbes, Amy E. Goldman, Manasi Simhan, Morgan E. Barnes, Maggi Laan, Sophia McKever, Z. Jason Hou, Xingyuan Chen, Timothy Scheibe, James Stegen

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Research influence of humidity on parameters of process separation grain lots in the pneumochannel of the machine preliminary clearing by N.S. DONTSOV, N.P. POGORELOV

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Applying the machine learning methods to determine the linear optics parameters in the ThomX collector ring by D. Klekots, O. Bezshyyko, L. Golinka-Bezshyyko, V. Kubytskyi, I. Chaikovska

“…As an alternative to the component-independent analysis, machine learning and neural networks are proposed for determining the beam parameters. …”
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MULTI-OBJECTIVE OPTIMIZATION OF THE MAIN DESIGN PARAMETERS OF THE HYDRAULIC CRANE-MANIPULATOR INSTALLATIONS OF MOBILE MACHINES by I. A. Lagerev, A. V. Lagerev

“…Presents a methodology for optimal design of crane-manipulator installations of mobile transport technological machines at the pre-design stage of development of the technical proposal. …”
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Effect of machining parameters on the mechanical properties of high dosage short carbon- fiber reinforced composites by S. E. Oliveira, J.A.M. Ferreira, J. da Silva

“…The machinability of polymer matrix composites with fibers strongly depends on the type of fiber and dosage in question, having a high influence on the selection of tools and cutting parameters. …”
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Predicting Marshall stability and flow parameters in asphalt pavements using explainable machine-learning models by Ibrahim Asi, Yusra I. Alhadidi, Taqwa I. Alhadidi

“…This study aims to predict these parameters using explainable machine-learning techniques. …”
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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This paper introduces the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a new tool designed with the aim of providing a simple and flexible framework to estimate the sensitivity and importance of parameters in complex numerical weather prediction models. …”
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Optimized Fake News Classification: Leveraging Ensembles Learning and Parameter Tuning in Machine and Deep Learning Methods by Abubaker A. Alguttar, Osama A. Shaaban, Remzi Yildirim

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PARAMETER DETERMINATION FOR ADDITIONAL OPERATING FORCE MECHANISM IN DEVICE FOR PNEUMO-CENTRIFUGAL MACHINING OF BALL-SHAPED WORKPIECES by A. A. Sukhotsky, I. P. Filonov, A. S. Kozeruk, M. I. Filonova

“…The paper describes development of the methodology for optimization of parameters for an additional operating force mechanism in a device for pneumo-centrifugal machining of glass balls. …”
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Multi-objective artificial-intelligence-based parameter tuning of antennas using variable-fidelity machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Stanislaw Szczepanski

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PARAMETRICAL PHENOMENA UNDER ON-MACHINE PROCESS CONTROL by Vilor Lavrentyevich Zakovorotniy, Pham Thu Huong, Pham Dinh Pham Dinh

“…Parameter changes are caused by cyclic variations of the workpiece stiffness in the direction normal to the rotative axis, as well as variations of the allowance for machining periodic with the period of its rotation. …”
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Survey of research on application of heuristic algorithm in machine learning by Yanping SHEN, Kangfeng ZHENG, Chunhua WU, Yixian YANG

“…Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs.…”
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Machine Learning Model for Hepatitis C Diagnosis Customized to Each Patient by Leran Chen, Ping Ji, Yongsheng Ma

Subjects: “…Machine learning…”
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Optimization Design and Experiment of Soil-Covering Device for Astragalus Mulching Transplanting Machine by Bin Feng, Wei Sun, Shanglong Xin, Guanping Wang, Wenjing Lv, Junzeng Wang

“…Firstly, based on the analysis of the overall structure of the transplanting machine, the structure and working principle of the soil-covering device are expounded, and the structure and working parameters of the soil-covering disc and soil-covering drum are clarified. …”
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Lumped parameter modeling and experimental characterization of pressure effects in a roller-type peristaltic pump with neoprene tubing for dialysis machines. by Carlo Carotenuto, Federico Ferrari, Stefano Salerno, Federico Bernabei, Wassim Lababidi, Luca Montorsi, Massimo Milani

“…Dialysis machines are vital devices for individuals with chronic kidney diseases, functioning as artificial kidneys to purify blood by removing waste and excess fluid. …”
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Reducing Mesh Dependency in Dataset Generation for Machine Learning Prediction of Constitutive Parameters in Sheet Metal Forming by Dário Mitreiro, Pedro A. Prates, António Andrade-Campos

Subjects: “…parameter identification…”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…A validated CFD model generated 935 numerical cases across diverse operational and design parameters, which were used to train and evaluate three machine learning algorithms: linear regression (LR), support vector regression (SVR), and artificial neural networks (ANN). …”
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Penerapan Machine Learning untuk Mengendalikan Parameter Budidaya Tanaman Hidroponik Berbasis Edge dan Cloud Computing by Helmy Helmy, Arif Nursyahid, Thomas Agung Setyawan

“…Keasaman larutan (pH) adalah parameter penting dalam budidaya hidroponik, karena mempengaruhi kemampuan tanaman menyerap unsur hara. …”
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