Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Transfer learning-based thermal error prediction and control with deep residual LSTM network
Jialan Liu, Chi Ma, Hongquan Gui, et al.
Knowledge-Based Systems (2021) Vol. 237, pp. 107704-107704
Closed Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Modeling and compensation of small-sample thermal error in precision machine tool spindles using spatial–temporal feature interaction fusion network
Qian Chen, Xuesong Mei, Jialong He, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102741-102741
Closed Access | Times Cited: 42
MA-CNN based spindle thermal error modeling using the depth feature analysis with thermal error mechanism
Guoqiang Fu, Sen Mu, Yue Zheng, et al.
Measurement (2024) Vol. 226, pp. 114183-114183
Closed Access | Times Cited: 12
A novel adaptive deep transfer learning method towards thermal error modeling of electric spindles under variable conditions
Xiaojuan Ma, Jiewu Leng, Zhuyun Chen, et al.
Journal of Manufacturing Systems (2024) Vol. 74, pp. 112-128
Closed Access | Times Cited: 11
Implementation of a Long Short-Term Memory Transfer Learning (LSTM-TL)-Based Data-Driven Model for Building Energy Demand Forecasting
Dongsu Kim, Yongjun Lee, Kyungil Chin, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 2340-2340
Open Access | Times Cited: 18
Thermal error modelling and compensation of CNC lathe feed system based on positioning error measurement and decoupling
Hu Shi, Boyang Zhang, Xuesong Mei, et al.
Measurement (2024) Vol. 231, pp. 114633-114633
Closed Access | Times Cited: 7
Science-based, data-driven developments in plasma processing for material synthesis and device-integration technologies
Makoto Kambara, Satoru Kawaguchi, Hae June Lee, et al.
Japanese Journal of Applied Physics (2022) Vol. 62, Iss. SA, pp. SA0803-SA0803
Open Access | Times Cited: 27
VMD-SEAE-TL-Based Data-Driven soft sensor modeling for a complex industrial batch processes
Jun-Chao Ren, Ding Liu, Yin Wan
Measurement (2022) Vol. 198, pp. 111439-111439
Closed Access | Times Cited: 24
Transfer learning applying electrochemical degradation indicator combined with long short-term memory network for flexible battery state-of-health estimation
Jaeyeong Kim, Dong‐Ho Han, Pyeong‐Yeon Lee, et al.
eTransportation (2023) Vol. 18, pp. 100293-100293
Closed Access | Times Cited: 16
Correlation analysis-based thermal error control with ITSA-GRU-A model and cloud-edge-physical collaboration framework
Qiang Yuan, Chi Ma, Jialan Liu, et al.
Advanced Engineering Informatics (2022) Vol. 54, pp. 101759-101759
Closed Access | Times Cited: 19
A spindle thermal error modeling based on 1DCNN-GRU-Attention architecture under controlled ambient temperature and active cooling
Guangjie Jia, Xu Zhang, Xingzhao Wang, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 127, Iss. 3-4, pp. 1525-1539
Closed Access | Times Cited: 12
Sequence-to-sequence based LSTM network modeling and its application in thermal error control framework
Shuang Zeng, Chi Ma, Jialan Liu, et al.
Applied Soft Computing (2023) Vol. 138, pp. 110221-110221
Closed Access | Times Cited: 11
Data-driven thermal error modeling based on a novel method of temperature measuring point selection
Haiyang Liu, Haigang Deng, Xianying Feng, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 131, Iss. 3-4, pp. 1823-1848
Closed Access | Times Cited: 4
Adaptive thermal error prediction for CNC machine tool spindle using online measurement and an improved recursive least square algorithm
Xinyuan Wei, Honghan Ye, Wang Gao, et al.
Case Studies in Thermal Engineering (2024) Vol. 56, pp. 104239-104239
Open Access | Times Cited: 4
Thermal error modeling of electric spindles based on cuckoo algorithm optimized Elman network
Ye Dai, Xin Wang, Zhaolong Li, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 132, Iss. 3-4, pp. 1365-1375
Closed Access | Times Cited: 4
Modeling of thermal errors in electric spindle based on a hybrid approach of thermal deformation theory and data drive
Yingqiang Zheng, Tao Tao, Xuesong Mei, et al.
Journal of Intelligent Manufacturing (2025)
Closed Access
Explaining multimodal CNN-DNN model predictions for quality monitoring of porosity in laser metal deposition
Vidita Gawade, Mengfei Chen
Knowledge-Based Systems (2025), pp. 113095-113095
Closed Access
Enhancing Spindle Precision: Thermal Error Modeling with Multi-parameter Optimization and Energy Consumption Data
Zhou Bo, Guohua Chen, Jie Mao, et al.
International Journal of Precision Engineering and Manufacturing (2025)
Closed Access
Temperature measuring points selection based on the effect of thermal deformation of components
Haiyang Liu, Xianying Feng, Yandong Liu, et al.
Case Studies in Thermal Engineering (2025), pp. 106009-106009
Open Access
Intelligent integrated framework towards high-accuracy machining
Lang Zhang, Jialan Liu, Chi Ma, et al.
Engineering Science and Technology an International Journal (2023) Vol. 40, pp. 101359-101359
Open Access | Times Cited: 10
A Regularized Regression Thermal Error Modeling Method for CNC Machine Tools under Different Ambient Temperatures and Spindle Speeds
Xinyuan Wei, Honghan Ye, Jinghuan Zhou, et al.
Sensors (2023) Vol. 23, Iss. 10, pp. 4916-4916
Open Access | Times Cited: 10
An axial attention-BiLSTM-based method for predicting the migration of CNC machine tool spindle thermal error under varying working conditions
Jiacheng Sun, Zhenyu Liu, Chan Qiu, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 130, Iss. 3-4, pp. 1405-1419
Open Access | Times Cited: 8
Industrial-oriented machine learning big data framework for temporal-spatial error prediction and control with DTSMGCN model
Hongquan Gui, Jialan Liu, Chi Ma, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 3, pp. 1173-1196
Closed Access | Times Cited: 7
An Improved Robust Thermal Error Prediction Approach for CNC Machine Tools
Honghan Ye, Xinyuan Wei, Xindong Zhuang, et al.
Machines (2022) Vol. 10, Iss. 8, pp. 624-624
Open Access | Times Cited: 12
Subspace Metric-Based Transfer Learning for Spindle Thermal Error Prediction Under Time-Varying Conditions
Haoyang Mao, Zhenyu Liu, Chan Qiu, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access | Times Cited: 2
Intermittent multivariate time series spindle thermal error prediction under wide environmental temperature ranges and diverse scenario conditions
Guangjie Jia, Xu Zhang, Yijun Shen, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 132, Iss. 9-10, pp. 4625-4643
Open Access | Times Cited: 2
Page 1 - Next Page

Scroll to top