Predictive modeling of PMMA-based polymer composites reinforced with hydroxyapatite: a machine learning and FEM approach by Rohit Kumar Singh, Khyati Verma, G. C. Mohan Kumar

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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…The aim of the study is to create neural network models of modules in an adaptive testing system to design an individual testing trajectory.The research article discusses the implementation of an adaptive testing system in terms of introducing artificial neural network modules into its composition, which should solve the problem of choosing a topic and the complexity of the next question, taking into account previous answers and the complexity of previously asked questions, as well as the connectivity of topics and response time as a factor guessing or searching for an answer, thereby forming an individual testing trajectory.Materials and methods. …”
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Research on Plant RNA-Binding Protein Prediction Method Based on Improved Ensemble Learning by Hongwei Zhang, Yan Shi, Yapeng Wang, Xu Yang, Kefeng Li, Sio-Kei Im, Yu Han

“…Accurate prediction of plant-specific RBPs is vital for understanding gene regulation and enhancing genetic improvement. (2) Methods: We propose an ensemble learning method that integrates shallow and deep learning. …”
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Deep Reinforcement Learning-Based Distribution Network Planning Method Considering Renewable Energy by Liang Ma, Chenyi Si, Ke Wang, Jinshan Luo, Shigong Jiang, Yi Song

“…The emergence of new artificial intelligence provides a new way to solve this problem. Based on the above discussion, this paper proposes a DNP method based on deep reinforcement learning (DRL). …”
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Intelligent text analysis for effective evaluation of english Language teaching based on deep learning by Yuan Ren, Wenjuan Fan, Jinhai Wang

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Predicting 3-year all-cause mortality in rectal cancer patients based on body composition and machine learning by Xiangyong Li, Zeyang Zhou, Xiaoyang Zhang, Xinmeng Cheng, Chungen Xing, Yong Wu

“…This study aimed to develop and validate a machine learning (ML) predictive model for 3-year all-cause mortality after laparoscopic total mesorectal excision (LaTME).MethodsPatients who underwent LaTME surgery between January 2018 and December 2020 were included and randomly divided into training and validation cohorts. …”
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Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures by Wei Tian, Hang Yuan, Xinpeng You, Hehui Zheng, Bazhou Li, Chengming Peng

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A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer by Xuebin Huang, Anfeng Xu, Hongbing Liu, Bingcheng Ye

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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…Aiming at the problems of large workload and low intelligence of the current infrared image-based overheating defect detection techniques for composite insulators, and the poor accuracy and poor generalization performance of the traditional image segmentation methods in complex backgrounds, an overheating defect detection method is proposed for composite insulators based on instance segmentation network Mask R-CNN. …”
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Research on online modeling of multiple demonstration trajectories for robots based on composite movement primitives by LI Zhiyong, YAN Bin, HUANG Xiaoping, LIU Changsheng, MA Cunguo, LIU Tundong

“…ObjectiveAiming at the problems of low parameter estimation efficiency and lack of multi-trajectory modeling ability in traditional robot demonstration learning algorithm, an online modeling method of robot multiple demonstration trajectories based on composite dynamical movement primitives was proposed.MethodsGaussian mixture model was used to model multi-demonstration trajectory in the composite algorithm. …”
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Low-cycle fatigue life prediction method for stud connectors based on interpretable machine learning by Jianan Pan, Xiaoling Liu, Bing Wang, Ying Liu

“…This study aims to develop a high-precision prediction model for low-cycle fatigue life using machine learning methods, providing a new approach for material performance evaluation. …”
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Quantitative Convolutional Neural Network Based Multi-Phase XRD Pattern Analysis by Höfer Hawo H., Orth André, Schweidler Simon, Breitung Ben, Aghassi-Hagmann Jasmin, Reischl Markus

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Composite Learning Prescribed Performance Control of Nonlinear Systems by Fang Zhu, Wei Xiang, Chunzhi Yang

“…Furthermore, novel composite learning laws are proposed to update NN weights based on a partial persistent excitation (PE) condition. …”
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Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning by Cuixia Liu, Meng Meng, Xian Luo

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Dry sliding tribological characteristics evaluation and prediction of TiB2-CDA/Al6061 hybrid composites exercising machine learning methods by Amit Aherwar, Anamika Ahirwar, Vimal Kumar Pathak

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A Novel Transformer-Based Approach for Reliability Evaluation of Composite Systems With Renewables and Plug-in Hybrid Electric Vehicles by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

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Epilepsy Diagnosis Analysis via a Multiple-Measures Composite Strategy from the Viewpoint of Associated Network Analysis Methods by Haoying Niu, Tiange Mu, Yuting Wang, Jiayang Huang, Jie Liu

“…Based on some typical complex network analysis methods and machine learning techniques, a general multiple-measures composited strategy-guided epilepsy diagnosis analysis framework is proposed in this brief paper. …”
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Thermographic Data Processing and Feature Extraction Approaches for Machine Learning-Based Defect Detection by Alexey Moskovchenko, Michal Svantner

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Fatigue strength prediction of Cobalt alloys using material composition and monotonic properties: ML-based approach by Subraya Krishna Bhat, Amritanshu Ranjan, Y S Upadhyaya, Vishwanath Managuli

“…In this study, we propose a machine learning (ML) based approach as an alternative to predict fatigue strength based on the published data available on material composition and monotonic loading properties (yield strength and ultimate tensile strength). …”
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Chemistry Learning Through CIRC on DNA Base Materials: Hypothesis Testing the Kolmogorov-Smirnov Method on Male and Female Population Samples by Endro Tri Susdarwono

“…The purpose of this study is to provide a description of learning chemistry through CIRC on DNA base material. …”
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