An LSTM-based predictive monitoring method for data with time-varying variability.

Authors: Qiu, Jiaqi^1,2 (AUTHOR) j.qiu@uva.nl, Lin, Yu^1,3 (AUTHOR), Zwetsloot, Inez M.^1,2 (AUTHOR)

Source: International Journal of Production Research. Apr2025, Vol. 63 Issue 7, p2622-2637. 16p.

Subject Terms: *Quality control charts, Long short-term memory, Recurrent neural networks, Deep learning, Detectors

Classifying distinct emotions from parents of ASD child using EEG source data by combining Bernoulli–Laplace Prior and graph neural networks.

Authors: ArulDass, Stephen Dass¹, Jayagopal, Prabhu¹, j.prabhu@vit.ac.in

Source: Neural Computing & Applications; Apr2025, Vol. 37 Issue 12, p7877-7895, 19p

Periodicity aware spatial-temporal adaptive hypergraph neural network for traffic forecasting.

Authors: Zhao, Wenzhu¹, wenzhu_zhao@cumt.edu.cn, Yuan, Guan^1,2, yuanguan@cumt.edu.cn, Bing, Rui¹, bingrui@cumt.edu.cn, Lu, Ruidong¹, luruidong@cumt.edu.cn, Shen, Yudong¹, shenyudong@cumt.edu.cn

Source: GeoInformatica; Apr2025, Vol. 29 Issue 2, p201-232, 32p

Decentralised protocols for autonomous mobile robots in material handling: inductive learnings from centralised controller.

Authors: Kim, Byeongmok¹ (AUTHOR) kim3453@purdue.edu, Kim, Yonggab¹ (AUTHOR), Lee, Seokcheon¹ (AUTHOR)

Source: International Journal of Production Research. Feb2025, Vol. 63 Issue 4, p1372-1398. 27p.

Subject Terms: *Artificial neural networks, *Artificial intelligence, *Materials handling, Autonomous robots, Mobile robots

A configuration optimization approach for reconfigurable manufacturing system based on column-generation combined with graph neural network.

Authors: Cui, Feng¹ (AUTHOR), Jiang, Zhibin^1,2,3 (AUTHOR), Zhou, Xin¹ (AUTHOR), Zheng, Junli^2,3 (AUTHOR), Geng, Na^2,3 (AUTHOR) gengna@sjtu.edu.cn

Source: International Journal of Production Research. Feb2025, Vol. 63 Issue 3, p970-991. 22p.

Subject Terms: *Column generation (Algorithms), *Inventory costs, Graph neural networks, Structural optimization, Stochastic programming

A hybrid ANN-MILP model for agile recovery production planning for PPE products under sharp demands.

Authors: Babazadeh, Reza¹ (AUTHOR) r.babazadeh@urmia.ac.ir, Taraghi Nazloo, Hanieh¹ (AUTHOR), Kamran, Mehdi A.² (AUTHOR)

Source: International Journal of Production Research. Jan2025, Vol. 63 Issue 2, p758-778. 21p.

Subject Terms: *Artificial neural networks, *Production planning, *Mathematical programming, *Mathematical optimization, *Artificial intelligence

Using graph neural network to conduct supplier recommendation based on large-scale supply chain.

Authors: Tu, Yuchun¹ (AUTHOR), Li, Wenxin¹ (AUTHOR), Song, Xiao¹ (AUTHOR), Gong, Kaiqi¹ (AUTHOR) ZB2039102@buaa.edu.cn, Liu, Lu² (AUTHOR), Qin, Yunhao¹ (AUTHOR), Liu, Songsong¹ (AUTHOR), Liu, Ming¹ (AUTHOR)

Source: International Journal of Production Research. Dec2024, Vol. 62 Issue 24, p8595-8608. 14p.

Subject Terms: *Supply chain disruptions, *Recommender systems, *Division of labor, Graph neural networks, Knowledge graphs

Modeling and Interpreting the Propagation Influence of Neighbor Information in Time-Variant Networks with Exemplification by Financial Risk Prediction.

Authors: Wang, Jianfei¹ (AUTHOR) wangjianfei9@126.com, Zhou, Lina² (AUTHOR) lzhou8@charlotte.edu, Jiang, Cuiqing^1,3 (AUTHOR) jiangcuiq2017@163.com, Wang, Zhao^1,4 (AUTHOR) xcwangzhao@163.com

Source: Journal of Management Information Systems. 2025, Vol. 42 Issue 1, p105-142. 38p.

Subject Terms: *Decision support systems, *Credit risk, *Artificial intelligence, *Recommender systems, Graph neural networks

Industrial internet platform-driven decentralised multi-level synchronised reconfiguration of assembly supply chains.

Authors: Huang, Hai-nan¹ (AUTHOR), Qu, Ting¹ (AUTHOR) quting@jnu.edu.cn, Qiu, Xiao-hui¹ (AUTHOR), Ma, Lin^1,2 (AUTHOR), Nie, Duxian³ (AUTHOR), Li, Congdong¹ (AUTHOR), Huang, George Q.^1,2,4 (AUTHOR)

Source: International Journal of Production Research. Jan2025, p1-23. 23p. 10 Illustrations.

Subject Terms: *Technological innovations, *Supply chains, *Information storage & retrieval systems, *Information architecture, Graph neural networks

Scheduling of steelmaking-continuous casting process by integrating deep neural networks with mixed integer programming.

Authors: Shin, Woo-Jin¹ (AUTHOR), Lee, Sang-Wook¹ (AUTHOR), Lee, Jun-Ho² (AUTHOR), Song, Min-Ho³ (AUTHOR), Kim, Hyun-Jung¹ (AUTHOR) hyunjungkim@kaist.ac.kr

Source: International Journal of Production Research. Dec2024, p1-22. 22p. 14 Illustrations.

Subject Terms: *Artificial neural networks, *Artificial intelligence, *Integer programming, *Flow shops, Training of engineers

Heterogeneous knowledge graph-driven subassembly identification with ensemble deep learning in Industry 4.0.

Authors: Zhang, Chao¹ (AUTHOR), Jing, Yanzhen¹ (AUTHOR), Zhou, Guanghui¹ (AUTHOR) ghzhou@mail.xjtu.edu.cn, Yan, Hairui¹ (AUTHOR), Chang, Fengtian² (AUTHOR)

Source: International Journal of Production Research. Dec2024, p1-17. 17p. 11 Illustrations.

Subject Terms: *Systems engineering, Graph neural networks, Deep learning, Knowledge graphs, Detection algorithms

A Spatial–Temporal Adaptive Graph Convolutional Network with Multi-Sensor Signals for Tool Wear Prediction.

Authors: Xia, Yu¹, xiayuyui@csu.edu.cn, Zheng, Guangji¹, Li, Ye¹, Liu, Hui¹, csuliuhui@csu.edu.cn

Source: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p2058, 24p

FabToys: Large Arrays of Fabric-Based Pressure Sensors in Plush Toys to Detect Fine-Grained Interaction.

Authors: Kiaghadi, Ali¹, akiaghadi@umass.edu, Huang, Jin¹, jinhuang@cs.umass.edu, Homayounfar, Seyedeh¹, shomayounfar@umass.edu, Andrew, Trisha¹, tandrew@umass.edu, Ganesan, Deepak¹, dganesan@cs.umass.edu

Source: Communications of the ACM; Apr2025, Vol. 68 Issue 4, p82-90, 9p

Enhanced Location Prediction for Wargaming with Graph Neural Networks and Transformers.

Authors: Liang, Dingge^1,2, dinggeliang@gmail.com, Li, Junliang², Yin, Junping^1,2,3, yinjp829829@126.com

Source: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p1723, 20p

CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer.

Authors: Liu, Kai^1,2, 622230830024@mails.cqjtu.edu.cnyangyang87@crecg.com, Ren, Tao^1,2, 622220070018@mails.cqjtu.edu.cnrentao3@crecg.com, Lan, Zhangli¹, rentao3@crecg.com, Yang, Yang², Liu, Rong³, cqjtu_liurong@cqjtu.edu.cn, Xu, Yuantong¹

Source: Buildings (2075-5309); Jan2025, Vol. 15 Issue 2, p197, 17p

AD-FGP: Industrial Multivariate Time-Series Anomaly Detection via Fusion of Generative and Predictive Models.

Authors: YONG JIN¹, 21051048@zju.edu.cn, YANG-HUA GAO¹, WEI-DONG LOU¹, ZE-LIANG ZHEN², gaoyh@zjtobacco.com, SHENG-DUO GAN², lotrwd@zjtobacco.com

Source: Journal of Information Science & Engineering; Jan2025, Vol. 41 Issue 1, p155-171, 17p

Methods and Applications of Data Management and Analytics.

Authors: Zhang, Wenjie¹, wenjie.zhang@unsw.edu.au, Yang, Zhengyi¹, zhengyi.yang@unsw.edu.au

Source: Applied Sciences (2076-3417); Dec2024, Vol. 14 Issue 24, p11637, 4p

Epilepsy EEG Seizure Prediction Based on the Combination of Graph Convolutional Neural Network Combined with Long- and Short-Term Memory Cell Network.

Authors: Kuang, Zhejun^1,2,3, 221501482@mails.ccu.edu.cn, Liu, Simin^1,2,3, Zhao, Jian^1,2,3, zhaojian@ccu.edu.cn, Wang, Liu^1,2,3, Li, Yunkai^1,2,3

Source: Applied Sciences (2076-3417); Dec2024, Vol. 14 Issue 24, p11569, 18p

Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting.

Authors: Singh, Vandana¹, phdcs10008.20@bitmesra.ac.invbhattacharya@bitmesra.ac.in, Sahana, Sudip Kumar¹, phdcs10008.20@bitmesra.ac.in, Bhattacharjee, Vandana¹

Source: Applied Sciences (2076-3417); Dec2024, Vol. 14 Issue 24, p11477, 18p

Introduction to Computational Advertising Research Methodology Themed Issue.

Authors: Huh, Jisu (AUTHOR) jhuh@umn.edu, Nelson, Michelle R. (AUTHOR), Russell, Cristel Antonia (AUTHOR)

Source: Journal of Advertising. Oct-Dec2024, Vol. 53 Issue 5, p639-643. 5p.

Subject Terms: *Artificial neural networks, *Influencer marketing, *Word of mouth advertising, *Location marketing, Generative artificial intelligence, Social media, Online social networks