Xiaorui Shao

530 total citations
23 papers, 381 citations indexed

About

Xiaorui Shao is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Xiaorui Shao has authored 23 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Electrical and Electronic Engineering, 7 papers in Control and Systems Engineering and 7 papers in Artificial Intelligence. Recurrent topics in Xiaorui Shao's work include Energy Load and Power Forecasting (7 papers), Machine Fault Diagnosis Techniques (6 papers) and Fault Detection and Control Systems (5 papers). Xiaorui Shao is often cited by papers focused on Energy Load and Power Forecasting (7 papers), Machine Fault Diagnosis Techniques (6 papers) and Fault Detection and Control Systems (5 papers). Xiaorui Shao collaborates with scholars based in South Korea, China and United States. Xiaorui Shao's co-authors include Chang Soo Kim, Chang-Soo Kim, Chang-Soo Kim, Dae Geun Kim, Chang H. Kim, Ilkyeun Ra, Yuming Li, Yanyan Liu, De Li and Ahyoung Lee and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Xiaorui Shao

21 papers receiving 368 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xiaorui Shao South Korea	10	131	121	78	49	45	23	381
Yi Ning China	9	120 0.9×	234 1.9×	92 1.2×	37 0.8×	50 1.1×	31	368
Yuxian Zhang China	12	134 1.0×	108 0.9×	57 0.7×	104 2.1×	22 0.5×	59	382
Khalil AL-Bukhaiti China	11	52 0.4×	203 1.7×	61 0.8×	36 0.7×	39 0.9×	48	466
Ziqian Kong China	7	259 2.0×	107 0.9×	60 0.8×	69 1.4×	16 0.4×	11	372
Seungmin Jung South Korea	10	73 0.6×	183 1.5×	90 1.2×	44 0.9×	42 0.9×	19	389
Wumaier Tuerxun China	7	119 0.9×	114 0.9×	78 1.0×	37 0.8×	14 0.3×	8	317
Renzhuo Wan China	6	40 0.3×	99 0.8×	70 0.9×	17 0.3×	70 1.6×	11	304
Kar Hoou Hui Malaysia	8	158 1.2×	48 0.4×	54 0.7×	95 1.9×	10 0.2×	19	311
Lilia Sidhom Tunisia	11	94 0.7×	158 1.3×	126 1.6×	35 0.7×	21 0.5×	45	379

Countries citing papers authored by Xiaorui Shao

Since Specialization

Citations

This map shows the geographic impact of Xiaorui Shao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaorui Shao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaorui Shao more than expected).

Fields of papers citing papers by Xiaorui Shao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaorui Shao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaorui Shao. The network helps show where Xiaorui Shao may publish in the future.

Co-authorship network of co-authors of Xiaorui Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaorui Shao. A scholar is included among the top collaborators of Xiaorui Shao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaorui Shao. Xiaorui Shao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Shao, Xiaorui, Ruizhang Huang, & Yongbin Qin. (2025). EnergyFormer: dual-supervised adaptive multi-scale Transformer for multistep energy forecasting. Expert Systems with Applications. 305. 130750–130750.

Shao, Xiaorui & Chang Soo Kim. (2025). Multi-branch global Transformer‐assisted network for fault diagnosis. Applied Soft Computing. 182. 113572–113572. 1 indexed citations

Wang, Yongjie, et al.. (2025). An efficient fire detection algorithm based on Mamba space state linear attention. Scientific Reports. 15(1). 11289–11289.

Shao, Xiaorui, De Li, Ilkyeun Ra, & Chang Soo Kim. (2024). DSMT-1DCNN: Densely supervised multitask 1DCNN for fault diagnosis. Knowledge-Based Systems. 292. 111609–111609. 7 indexed citations

Shao, Xiaorui & Chang Soo Kim. (2024). TFFS: A trainable federal fusion strategy for multistep time series forecasting. Information Sciences. 679. 121126–121126. 3 indexed citations

Shao, Xiaorui, et al.. (2024). GAILS: an effective multi-object job shop scheduler based on genetic algorithm and iterative local search. Scientific Reports. 14(1). 2068–2068. 6 indexed citations

Shao, Xiaorui & Chang Soo Kim. (2023). Adaptive multi-scale attention convolution neural network for cross-domain fault diagnosis. Expert Systems with Applications. 236. 121216–121216. 53 indexed citations

Shao, Xiaorui, Ahyoung Lee, & Chang Soo Kim. (2023). DL-MSCNN: a general and lightweight framework for fault diagnosis with limited training samples. Journal of Intelligent Manufacturing. 36(1). 147–166. 5 indexed citations

Li, Yuming, et al.. (2022). A lightweight network for real-time smoke semantic segmentation based on dual paths. Neurocomputing. 501. 258–269. 12 indexed citations

10.

Shao, Xiaorui & Chang-Soo Kim. (2022). Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing. Sensors. 22(11). 4156–4156. 35 indexed citations

11.

Shao, Xiaorui & Chang Soo Kim. (2022). An Adaptive Job Shop Scheduler Using Multilevel Convolutional Neural Network and Iterative Local Search. IEEE Access. 10. 88079–88092. 3 indexed citations

12.

Shao, Xiaorui & Chang Soo Kim. (2021). Accurate Multi-Site Daily-Ahead Multi-Step PM2.5 Concentrations Forecasting Using Space-Shared CNN-LSTM. Computers, materials & continua/Computers, materials & continua (Print). 70(3). 5143–5160. 14 indexed citations

13.

Shao, Xiaorui & Chang Soo Kim. (2021). A Hybrid Deep Learning Scheme for Multi-Channel Sleep Stage Classification. Computers, materials & continua/Computers, materials & continua (Print). 71(1). 889–905. 19 indexed citations

14.

Shao, Xiaorui & Chang H. Kim. (2021). Self-Supervised Long-Short Term Memory Network for Solving Complex Job Shop Scheduling Problem. KSII Transactions on Internet and Information Systems. 15(8). 8 indexed citations

15.

Shao, Xiaorui, et al.. (2021). Highly Accurate Short-Term Gas Consumption and Elapsed Time Forecasting Using Multi-Channel Deep Neural Network. IEEE Access. 9. 157447–157457. 3 indexed citations

16.

Shao, Xiaorui, Chang Soo Kim, & Dae Geun Kim. (2020). Accurate Multi-Scale Feature Fusion CNN for Time Series Classification in Smart Factory. Computers, materials & continua/Computers, materials & continua (Print). 65(1). 543–561. 23 indexed citations

17.

Shao, Xiaorui, et al.. (2020). Accurate Deep Model for Electricity Consumption Forecasting Using Multi-Channel and Multi-Scale Feature Fusion CNN–LSTM. Energies. 13(8). 1881–1881. 57 indexed citations

18.

Shao, Xiaorui & Chang Soo Kim. (2020). Multi-Step Short-Term Power Consumption Forecasting Using Multi-Channel LSTM With Time Location Considering Customer Behavior. IEEE Access. 8. 125263–125273. 49 indexed citations

19.

Shao, Xiaorui, et al.. (2019). A Study on Customers’ Sentiment Analysis Based on Big Data Using Twitter Data. International Journal of Computer Theory and Engineering. 11(1). 11–14. 8 indexed citations

20.

Shao, Xiaorui, et al.. (2019). Traffic Accident Time Series Prediction Model Based on Combination of ARIMA and BP and SVM. 41–46. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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