Ghungzhou, China

Ming Ye




Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2019

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1 patent (USPTO):

Title: The Innovative Mind of Ming Ye

Introduction

Ming Ye is a prominent inventor based in Guangzhou, China. He has made significant contributions to the field of power distribution through his innovative patent. His work focuses on enhancing the efficiency and reliability of distribution transformers, which are crucial for electrical systems.

Latest Patents

Ming Ye holds a patent for a "Power distribution transformer load prediction analysis system." This system is designed to generate heavy load pre-warnings or overload pre-warnings for distribution transformers. The operation of the system includes selecting data records from various data sources, converting these records into different formats, and filtering them using predetermined thresholds. The system matches filtered records with specific distribution transformers and transforms the matched data into predefined predictor variables. It also involves selecting a subset of these variables, training and testing a model, and forecasting heavy load or overload conditions for transformers in a designated region. Ming Ye's innovative approach addresses critical challenges in power distribution management.

Career Highlights

Ming Ye is currently employed at Accenture Global Services GmbH, where he applies his expertise in developing advanced systems for power distribution. His work has been instrumental in improving the operational efficiency of electrical systems, making him a valuable asset to his organization.

Collaborations

Ming Ye collaborates with talented professionals such as Li Wang and Qin Zhou. Their combined efforts contribute to the advancement of technology in the field of power distribution.

Conclusion

Ming Ye's innovative contributions to power distribution technology exemplify the impact of dedicated inventors in enhancing electrical systems. His patent for a load prediction analysis system showcases his commitment to improving efficiency and reliability in the industry.

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