Impact wear behavior of austenitic steel bucket teeth based on machine learning by Zhihui Cai, Jianfeng Yan, Yandong Qiao, Rongjie Li, Yanchun Shi, Junping Zhang, Zhixiong Zhang

“…Using a random forest approach, the critical parameters influencing wear depth were identified. A particle swarm optimization support vector machine was employed to accurately predict wear depth. …”
Get full text

The Combined Internal and Principal Parametric Resonances on Continuum Stator System of Asynchronous Machine by Baizhou Li, Qichang Zhang

“…With the increasing requirement of quiet electrical machines in the civil and defense industry, it is very significant and necessary to predict the vibration and noise characteristics of stator and rotor in the early conceptual phase. …”
Get full text

Type-2 Fuzzy Logic Controller of a Doubly Fed Induction Machine by Keltoum Loukal, Leila Benalia

Get full text

Machine Learning Analysis of Arterial Oscillograms for Depression Level Diagnosis in Cardiovascular Health by Vladislav Kaverinsky, Dmytro Vakulenko, Liudmyla Vakulenko, Kyrylo Malakhov

“…By incorporating ULF parameters, products of correlated parameters, and additional measured factors, the classifier achieved high reliability in estimating depression levels. …”
Get full text

Sensorless Auto Commissioning of the Position Phase Shift Compensation in Permanent Magnet Machines by Kamel Saleh, Mark Sumner

“…An automated self commissioning procedures for sensorless controlled AC drives is described where no prior knowledge of the motor parameters is required. The procedures includes the sensorless automatic calculation of the mechanical parameters of the motor drive passing through the sensorless automatic design of the sensorless speed controller and the mechanical observer and finally the sensorless automatic compensation of the error between the tracked saturation saliency position and the real rotor position in the permanent magnet machines due to the armature reaction based on a new technique depends on injecting a pulse of current in the d_axis, the change in the current in q_axis will depend on the error between the saturation saliency position and the real rotor position. …”
Get full text

Research and application of VoLTE video call quality based on machine learning by Qizhu ZHONG

“…To overcome the shortcomings of current methods for evaluating VoLTE video call quality,a method for evaluating VoLTE video call quality without reference based on machine learning and network index parameters was proposed.Firstly,the network parameters of the decoding core network were collected and preprocessed; then,the key features for VoLTE video call quality assessment were selected,and a reference-free evaluation model for VoLTE video quality assessment was constructed by comparing and selecting appropriate machine learning algorithms,so as to achieve real-time VoLTE video call quality assessment independent of the test environment and the original video.By researching the preprocessing of feature index data extracted from XDR data,the standardization of feature index was solved,and the evaluation model of feature input was convenient; the key features of VoLTE video call were selected and evaluated by feature engineering,which reduced the feature dimension and the complexity of the algorithm; at the same time,advanced machine learning technology was adopted to ensure and enhance the algorithm assessment accuracy.…”
Get full text

Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis by Zishen Zhang, Hong Cheng, Meiyu Chen, Lixin Zhang, Yudou Cheng, Wenjuan Geng, Junfeng Guan

“…Spectral data within the 398~1004 nm wavelength range were analyzed to compare the predictive performance of the Least Squares Support Vector Machine (LS-SVM) models on various quality parameters, using different preprocessing methods and the selected feature wavelengths. …”
Get full text

Development and Research of the MZU­20D Air­Sieve Grain Cleaning Machine by P. A. Savinykh, Yu. V. Sychugov, V. A. Kazakov

“…The authors analyzed the working process and design of the machines involved in grain cleaning. It was revealed that the energy intensity of universal air-sieve machines of domestic and foreign production is 0.86-1.61 kilowatt-hours per ton, the specific metal consumption is 30-700 kilogram-hours per ton.…”
Get full text

Mathematical modeling of angular displacements of the base machine of a twoconsole sprinkler unit by T. G. Gasanov, E. Z. Batmanov, M. R. Guseynov, M. T. Mutalibov

“…The results of the study make it possible to evaluate the technical parameters of the angular displacements of the base machine on the magnitude of the impacts that disturb the unit.Conclusion. …”
Get full text

Exploration of ductility for refractory high entropy alloys via interpretive machine learning by Shaolong Zheng, Lingwei Yang, Liyang Fang, Chenran Xu, Guanglong Xu, Yifang Ouyang, Xiaoma Tao

“…Two ML algorithms, decision tree (DT) and CatBoost, are trained using physical parameters, with CatBoost demonstrating superior performance in RHEA ductility classification. …”
Get full text

Sensorless method of controlling the position of the movable element of the electric machine of the reciprocating action of by R. R. Gibadullin, A. N. Tsvetkov, I. V. Ivshin, L. V. Dolomanyuk

“…The article describes a Sensorless method for determining the position of the movable element electrical machines reciprocating action. The method is implemented on the basis of the data voltages of the windings and the results of measurements of parameters of electrical machines reciprocating action.…”
Get full text

Advancing crop recommendation system with supervised machine learning and explainable artificial intelligence by Sourabh Shastri, Sachin Kumar, Vibhakar Mansotra, Rohit Salgotra

“…Thus, there is a need to increase crop productivity, and machine learning (ML) techniques are very helpful in recommending suitable crops based on soil, weather, and other parameters. …”
Get full text

Smartphone-Based Pupillometry Using Machine Learning for the Diagnosis of Sports-Related Concussion by Anthony J. Maxin, Bridget M. Whelan, Michael R. Levitt, Lynn B. McGrath, Kimberly G. Harmon

“…All combinations of the seven PLR parameters were tested in machine learning binary classification models to determine the optimal combination for differentiating between non-concussed and concussed athletes. …”
Get full text

The Technical and Economic Aspects of Using DC or AC Motors in the Drive of Hoisting Machines by Tomasz Siostrzonek, Jacek Pytel, Tomasz Karpiel

“…Four motors that could potentially be used to build a hoisting machine with the assumed parameters were analysed. …”
Get full text

Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…In the present work, we combine machine learning (ML) algorithms and finite element simulation to predict the power confinement ( $$\hbox {P}_{conf}$$ ) and mode effective index ( $$\hbox {n}_{eff}$$ ) of slot waveguides with respect to geometric parameters such as gap, slab width, and slab height. …”
Get full text

Evaluating the slope behavior for geophysical flow prediction with advanced machine learning combinations by Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh, Viroon Kamchoom

“…Overall, the present research models outperformed the eleven (11) models of the previous work due to sorting and elimination of unrealistic data entries deposited in the literature, the application of dimensionless combination of the studied slope stability parameters and the superiority of the selected machine learning techniques.…”
Get full text

Risk assessment of oral leukoplakia by DNA content enhanced by machine learning models by Matheus Henrique Lopes Dominguete, Vera Cavalcanti de Araújo, Fernanda Viviane Mariano, Carmen Silvia Passos Lima, João Figueira Scarini, Paulo de Camargo Moraes, Victor Angelo Martins Montalli, Larissa Agatti, Zuraiza Mohamad Zaini, Luíza Hellmeister, Marcelo Sperandio

Get full text

Influence disabling the cylynders of internal combustion engine on working process earthmovers machines by S. S. Zhuravlev

“…The article considers the effects of disabling the cylinder to change the characteristics of the engine earth-moving machines in various operating modes, calculated the diesel engines with subsequent analysis of their performance under different algorithms disable cylinders, evaluated the possibility of using additional flywheel to increase the technological parameters of the machine during operation.…”
Get full text

Increasing Minority Recall Support Vector Machine Model for Imbalanced Data Classification by Chunye Wu, Nan Wang, Yu Wang

“…In the experiments, the effects of different parameters on the performance of the algorithm were analyzed, and the optimal parameters for a recall rate of 1 were determined. …”
Get full text

Prediction of Enthalpy of Mixing of Binary Alloys Based on Machine Learning and CALPHAD Assessments by Shuangying Huang, Guangyu Wang, Zhanmin Cao

“…Using pure element properties and Miedema’s model parameters as descriptors, we trained and evaluated four machine learning algorithms, finding LightGBM to perform best (R² = 92.2%, MAE = 3.5 kJ/mol). …”
Get full text