Jinan, China

Che Liu

This inventor holds 1 USPTO granted patent. Top assignee: Shandong University. Active years: 2023.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Che Liu. Retrieved from https://idiyas.com/inventor/che-liu-yox21awu

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

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% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Che Liu - Innovator in Building Energy Consumption Prediction

Introduction

Che Liu is a notable inventor based in Jinan, China. He has made significant contributions to the field of energy consumption prediction, particularly in building management. His innovative approach combines advanced modeling techniques to enhance energy efficiency in buildings.

Latest Patents

Che Liu holds a patent titled "Method and system for predicting building energy consumption based on Holt-Winters and extreme learning machine." This patent outlines a comprehensive method for predicting energy consumption in buildings. The process involves constructing a building simulation model using actual operational parameters to generate an original energy consumption data set. The data set is then decomposed into linear and nonlinear components, allowing for precise predictions using a trained Holt-Winters model and an extreme learning machine.

Career Highlights

Che Liu is affiliated with Shandong University, where he contributes to research and development in energy management systems. His work focuses on integrating machine learning techniques with traditional modeling approaches to improve the accuracy of energy consumption forecasts.

Collaborations

Che Liu has collaborated with colleagues such as Chenghui Zhang and Bo Sun. Their joint efforts have further advanced the research in building energy consumption prediction.

Conclusion

Che Liu's innovative methods and dedication to improving energy efficiency in buildings highlight his role as a significant contributor to the field. His patent demonstrates the potential of combining machine learning with traditional modeling techniques to achieve better energy management solutions.

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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