Prediction Method for Mechanical Characteristic Parameters of Weak Components of 110 kV Transmission Tower under Ice-Covered Condition Based on Finite Element Simulation and Machine Learning by Lin Yang, Lulu Mei, Yifei Chen, Yanpeng Hao, Licheng Li, Jianrong Wu, Xianyin Mao

“…Aiming at the lack of research on predicting mechanical characteristic parameters of weak components of transmission towers, and the cumbersome steps of building a finite element model (FEM), the study of prediction for mechanical characteristic parameters of weak components of towers based on a finite element simulation and machine learning is proposed. …”
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Development and validation of an interpretable machine learning model for predicting Philadelphia chromosome-positive acute lymphoblastic leukaemia using clinical and laboratory parameters: a single-centre retrospective study by Jing Zhang, Cheng Zhang, Xi Zhang, Wuchen Yang, Jingya Liu, Yang Gou, Xingqin Huang, Maoshan Chen, Dezhi Huang, Shengwang Wu, Shuiqing Liu, Xiangui Peng

“…Multiple machine learning (ML) models were constructed and optimised by using the active learning (AL) algorithm. …”
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Machine Learning-Based Recommender System for Pulsed Laser Ablation in Liquid: Recommendation of Optimal Processing Parameters for Targeted Nanoparticle Size and Concentration Using Cosine Similarity and KNN Models by Anesu Nyabadza, Dermot Brabazon

“…The current literature offers limited application of machine learning (ML), particularly recommender systems, in PLAL optimization and automation. …”
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Personalized prediction of breast cancer candidates for Anti-HER2 therapy using 18F-FDG PET/CT parameters and machine learning: a dual-center study by Zhenguo Sun, Jianxiong Gao, Wenji Yu, Xiaoshuai Yuan, Peng Du, Peng Chen, Yuetao Wang

“…The purpose of this study was to assess the performance of a machine learning (ML) model that was developed using 18F-FDG PET/CT parameters and clinicopathological features in distinguishing different levels of HER2 expression in breast cancer.MethodsThis retrospective study enrolled breast cancer patients who underwent 18F-FDG PET/CT scans prior to treatment at Lianyungang First People’s Hospital (centre 1, n=157) and the Third Affiliated Hospital of Soochow University (centre 2, n=84). …”
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Application of the program for artificial intelligence analytics of paper text and segmentation by specified parameters in clinical practice by A. A. Komkov, V. P. Mazaev, S. V. Ryazanova, A. A. Kobak, E. V. Bazaeva, D. N. Samochatov, E. V. Koshkina, Е. V. Bushueva, O. M. Drapkina

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A Review on Machine Learning Models in Injection Molding Machines by Senthil Kumaran Selvaraj, Aditya Raj, R. Rishikesh Mahadevan, Utkarsh Chadha, Velmurugan Paramasivam

“…Hence, there is a need for more close control over these operating parameters using various machine learning techniques. …”
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Machine Training of the System of Functional Diagnostics of the Shaft Lifting Machine by Dovbysh A. S., Zimovets V. I., Zuban Y. A., Prikhodchenko A. S.

“…The aim of the work is to increase the accuracy of functional diagnostics of a mine hoist by us-ing the method of information-extreme machine teaching with a hierarchical data structure. …”
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Grid-search method for short-term over long-term average parameter tuning: an application to Stromboli explosion quakes by Andrea Di Benedetto, Andrea Di Benedetto, Anna Figlioli, Anna Figlioli, Antonino D’Alessandro, Giosue’ Lo Bosco, Giosue’ Lo Bosco

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Identification of parameters of three-phase asynchronous motor when changing the initial values of the estimates in a wide range by A. J. Afanasiev, V. G. Makarov, V. N. Khannanova

Subjects: “…identification of parameters…”
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optRF: Optimising random forest stability by determining the optimal number of trees by Thomas M. Lange, Mehmet Gültas, Armin O. Schmitt, Felix Heinrich

Subjects: “…Parameter optimisation…”
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SPREAD: A large-scale, high-fidelity synthetic dataset for multiple forest vision tasks by Zhengpeng Feng, Yihang She, Srinivasan Keshav

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Fault Diagnosis Method for Rolling Bearing based on Least Squares Mapping and SVM by Zhao Yu, Li Ke, Su Lei, Chen Peng

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Preliminary Experimental Comparison of Plunge Milling and Face Milling: Influences of Cutting Parameters on Cutting Force and Surface Roughness by Afraa Khattab, István Sztankovics, Csaba Felhő

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Exploring the Influence of Pottery Jar Formula Variables on Flavor Substances Through Feature Ranking and Machine Learning: Case Study of Maotai-Flavored Baijiu by Haili Yang, Xinjun Hu, Jianpin Tian, Liangliang Xie, Manjiao Chen, Dan Huang

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Optimizing Time-Constrained Multi-Objective Process Parameters for Thin-Walled Maraging Steels Manufactured by Laser Powder Bed Fusion (LPBF) by Yeo-Ul Song, Byeong Uk Song, Joon Phil Choi, Min-Kyo Jung, Taeho Ha, Pil-Ho Lee

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Ink synthesis and inkjet printing of manganese electrodes on laser textured aluminium foil: The effect of laser texturing parameters on surface roughness and printability by Anesu Nyabadza, Suman Chatterjee, Suganya Pitchai Muthusamy, Sean Ryan, Jesus Inocente Medina Santos, Valeria Nicolosi, Dermot Brabazon, Mercedes Vazquez

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Recent advance in laser powder bed fusion of Ti–6Al–4V alloys: microstructure, mechanical properties and machinability by Chenbing Ni, Junjie Zhu, Baoguo Zhang, Kai An, Youqiang Wang, Dejian Liu, Wei Lu, Lida Zhu, Changfu Liu

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Classification-Based Parameter Optimization Approach of the Turning Process by Lei Yang, Yibo Jiang, Yawei Yang, Guowen Zeng, Zongzhi Zhu, Jiaxi Chen

“…The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. …”
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Investigation of the Effects of 3D Printing Parameters on the Mechanical Properties of Bone Scaffolds: Experimental Study Integrated with Artificial Neural Networks by Rixiang Quan, Sergio Cantero Chinchilla, Fengyuan Liu

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Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…This study explores the optimization of the machining time in CNC milling machines by varying the machine parameters and toolpath strategies. …”
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