Analyzing the compressive performance of lightweight foamcrete and parameter interdependencies using machine intelligence strategies by Wang Guoyuan, Fan Wenbo, Shi Qingbin, Luo Yingqi

“…For this purpose, the compressive strength (C-S) of foamcrete was assessed using two machine learning algorithms: gene expression programming (GEP) and multi-expression programming (MEP). …”
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Research on Machining Parameter Optimization and an Electrode Wear Compensation Method of Microgroove Micro-EDM by Xiaodong Zhang, Wentong Zhang, Peng Yu, Yiquan Li

“…Therefore, based on an established L27 orthogonal experiment, this paper uses the grey relational analysis (GRA) method to realize multi-objective optimization of machining time and electrode wear, so as to achieve the shortest machining time and the minimum electrode wear during machining under the optimal machining parameter combination. …”
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Structural Parameter Optimization of a Tubular Permanent-Magnet Linear Machine for Regenerative Suspension by Dongsheng Lu, Hailong Zhang, Jian Liu, Enrong Wang

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Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

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Investigation and Process Parameter Optimization on Wire Electric Discharge Machining of Aluminium 6082 Alloy by G. Murali, M. Murugan, K. Arunkumar, P. V. Elumalai, D. Mohanraj, S. Prabhakar

“…The factorial design was used for the selection of parameter levels and arrived at the 27 trails for the machining. …”
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Calculation parameter correction of steel truss nodal plate based on machine learning theory by Zhe Hu, Rui Rao, Hao Chen, Qinhe Li, Ronghui Wang

“…A digital twin is established for each control parameter of the nodal plate, and the rigid arm lengths are adjusted to achieve displacement matching with a high-precision plate element model. …”
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Parameter Prediction for Metaheuristic Algorithms Solving Routing Problem Instances Using Machine Learning by Tomás Barros-Everett, Elizabeth Montero, Nicolás Rojas-Morales

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Identification of dynamics for machining systems by Yuri Petrakov, Oleksandr Okhrimenko, Maksim Sikailo

Subjects: “…machining system…”
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Evaluation of Machine Learning Models for Enhancing Sustainability in Additive Manufacturing by Waqar Shehbaz, Qingjin Peng

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Research of Optimization of Grinding Parameter of Hypoid Gear based on Orthogonal Experiment by Mo Yimin, Li Qiming, Yang Junjian, Liu Jie, Huang Yecai

“…Grinding machining is the final procedure in the machining process of the hypoid gear. …”
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Impact of Channel and System Parameters on Performance Evaluation of Frequency Extrapolation Using Machine Learning by Michael Neuman, Daoud Burghal, Andreas F. Molisch

“…Over the past years, various machine learning (ML) techniques have been proposed for this goal, but their effectiveness is usually evaluated only for a limited number of examples. …”
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Develop Approach to Predicate Software Reliability Growth Model Parameters Based on Machine learning by anfal A. Fadhil, Asmaa’ H. AL_Bayati, Ibrahim Ahmed Saleh

“…The parameters are evaluated using three algorithms: machine learning decision tree (DT), support vector machine (SVM), and K-nearest neighbors (K-NN). …”
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Interaction of Machining Parameters on MRR of Sintered NdFeB Processed by EDM-Milling by Xinyu Zhang, Xue Bai, Tingyi Yang, Li Li

“…Sintered Neodymium–iron–boron (NdFeB) exhibits high hardness and brittleness, resulting in low electrical discharge machining (EDM) efficiency. The study on the interaction effect of parameters on the material removal rate (MRR) of sintered NdFeB processed by EDM-milling is carried out to improve machining efficiency. …”
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Theoretical background of the operating parameters of the satellite working mechanism of the hydraulic positive displacement machine by Pawel Sliwinski

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Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms by Arunadevi M, Karthikeyan B, Anirudh Shrihari, Saravanan S, Sundararaju K, R Palanisamy, Mohamed Awad, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Hany S. Hussein, Mahmoud M. Hussein, Ahmed I. Omar

“…It is clearly observed that the system temperature has significant percentage contribution as 96.92% on FC current and 86.22% on FC voltage compared to other parameters. Different MLAs are modelled to explore the PEMFC performance and results proved that gradient boosting regression provides better predictions compared to other algorithms such as decision tree regressor, support vector machine regressor, and random forest regression.…”
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Optimizing EDM process parameters with the use of GRA-based RSM for machining titanium alloy by Velusamy Mohankumar, Marudhamuthu Shanmugam Senthil Kumar, Aruchamy Karthik, Amanuel Kumsa Bojer, Enas Ali, Sherif S.M. Ghoneim, Ahmed B. Abou Sharaf

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Application of Machine Learning in Predicting Quality Parameters in Metal Material Extrusion (MEX/M) by Karim Asami, Maxim Kuehne, Tim Röver, Claus Emmelmann

“…However, achieving high-quality MEX/M parts requires significant experimental and financial investments for suitable parameter development. In response, this study explores the application of machine learning (ML) to predict the surface roughness and density in MEX/M components. …”
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The Effects of Cutting Pick Parameters on Cutting Head Performance in Tunneling–Bolting Combined Machines by Bo Ning, Mingzhu Li, Jinhua Zhang

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Experimental and computational investigation of the effect of machining parameters on the turning process of C45 steel by Tien-Thinh Le, Hang Thi Pham, Hiep Khac Doan, Panagiotis G. Asteris

“…In this study, experimental investigations and simulations were conducted to examine the influence of machining parameters during the turning process of C45 medium carbon steel, with the simultaneous application of the Johnson-Cook plasticity model and Johnson-Cook damage model. …”
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Influence of the Level of Defective Insulation Resistance of Electrical Machine Windings on Parameters of no-Load Current by A. V. Isaev, Yu. V. Suhodolov, S. V. Sizikov, A. A. Lomtev, V. A. Lychkovsky

“…The paper presents the results of experimental studies of the patterns of influence of the level of defective resistance of interturn insulation in the windings of electric machines on the parameters of the no-load current, including the features of changes in the parameters of its spectral components. …”
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