Chongqing, China

Shengjun Guo

This inventor holds 1 USPTO granted patent. Top assignee: Ccteg Chongqing Research Institute. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Shengjun Guo. Retrieved from https://idiyas.com/inventor/shengjun-guo-cr0bo8vf

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Shengjun Guo and Coal Mine Multi-Disaster Early Warning

Introduction

Shengjun Guo is an inventor based in Chongqing, China. His patent work addresses coal mine safety through methods for analyzing and forecasting multiple disaster risks.

Latest Patents

Guo is associated with 1 patent: “Multi-disaster fusion natural fission early warning method and system in coal mine.” The invention develops a relationship network among early-warning entities and updates it according to defined rules. It uses an LSTM artificial neural network to predict monitoring trends and applies natural-fission analysis rules to assess potential links between disaster indicators.

When the system detects an anomaly in an early-warning index, it evaluates other disaster indexes using depth-first traversal and natural-fission rules to support targeted forecasting. By building predictive relationships among indicators through correlation analysis, the method aims to enable multidimensional analysis and earlier trend prediction.

Career Highlights

Guo is associated with CCTEG Chongqing Research Institute. His patent reflects work focused on applying predictive models and interconnected risk indicators to coal mine disaster analysis.

Collaborations

The supplied information lists Haitao Sun and Zhigang Zhang as Guo’s coworkers. Their specific roles in the patent or related research are not provided.

Conclusion

Shengjun Guo’s coal mine early-warning invention combines trend prediction, anomaly detection, and analysis of relationships among disaster indicators to support more comprehensive safety forecasting.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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