Ruijie Chen

Title: Ruijie Chen and Data-Driven Equipment Benchmark Prediction.

Introduction

Ruijie Chen is an inventor based in Shanghai, China. Her patent work focuses on applying machine-learning methods to improve equipment performance analysis and automation.

Latest Patents

Chen is named on one patent, Method for Predicting Benchmark Value of Unit Equipment Based on XGBoost Algorithm and System Thereof. The invention uses historical equipment-operation data to build a dataset, applies random forest out-of-bag estimates to assess feature importance, removes less useful features, and standardizes the remaining data. It then uses Bayesian hyperparameter optimization to develop an XGBoost prediction model, which can estimate benchmark values for equipment parameters from real-time operating data. The described approach aims to improve prediction accuracy, generalization, processing speed, and the automation of unit operations. Chen’s listed patent count is 1 patent.

Career Highlights

Chen is associated with Huaneng Shanghai Combined Cycle Power Co., Ltd. Her patent reflects an application of machine learning to operational data, with the goal of establishing more reliable equipment benchmarks.

Collaborations

The supplied information lists Yongkang Wang and Gang Xu as Chen’s coworkers. It does not specify their roles in the patent or describe the nature of their collaboration.

Conclusion

Ruijie Chen’s patent applies XGBoost and feature-selection techniques to predict equipment benchmark values, connecting data-driven analysis with improved power-plant operations.