Yi Gong

Title: Yi Gong and Data-Driven Equipment Benchmark Prediction.

Introduction

Yi Gong is an inventor based in Shanghai, China. His patent work includes a method for predicting benchmark values for unit equipment using the XGBoost algorithm, with the aim of improving the accuracy and automation of equipment assessment.

Latest Patents

Gong is associated with 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 estimation to identify and remove less important features, and standardizes the remaining data. It then uses the dataset to train an XGBoost model, with Bayesian hyperparameter optimization, to predict benchmark values for equipment parameters from real-time operating data. The described approach is intended to improve prediction accuracy, generalization, and processing speed while increasing automation in unit operations. Gong’s listed portfolio comprises 1 patent.

Career Highlights

Gong’s patent focuses on applying machine-learning techniques to equipment operations. By combining feature selection, data standardization, and model optimization, the invention offers a data-driven approach to estimating equipment benchmarks.

Collaborations

Gong is associated with Huaneng Shanghai Combined Cycle Power Co., Ltd. His listed coworkers include Yongkang Wang and Gang Xu.

Conclusion

Yi Gong’s patent applies XGBoost and related data-processing methods to predict equipment benchmark values, reflecting an effort to improve operational assessment and automation.