This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Zhejiang University. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Zhile Yang: Innovator in Adaptive-Learning Intelligent Scheduling
Introduction
Zhile Yang is a prominent inventor based in Hangzhou, China. He has made significant contributions to the field of industrial production through his innovative patent. His work focuses on enhancing the efficiency of personalized customized production using advanced technologies.
Latest Patents
Zhile Yang holds a patent for an "Adaptive-learning intelligent scheduling unified computing frame and system for industrial personalized customized production." This invention utilizes a deep neural network and reinforcement learning to optimize production tasks. The system employs an optimization algorithm selected through automatic decision-making, which is based on a global customized production task. It integrates an industrial big data module to generate a global optimal static scheduling plan. The system monitors dynamic events in real time and adjusts scheduling accordingly, ensuring efficient production processes.
Career Highlights
Zhile Yang is affiliated with Zhejiang University, where he contributes to research and development in intelligent systems. His work has garnered attention for its innovative approach to solving complex scheduling problems in industrial settings. With a focus on adaptive learning, he aims to improve production efficiency and responsiveness.
Collaborations
Zhile Yang collaborates with notable colleagues, including Yue Chao and Dongsheng Yang. Their combined expertise enhances the research and development efforts at Zhejiang University, fostering innovation in the field of intelligent scheduling.
Conclusion
Zhile Yang's contributions to adaptive-learning intelligent scheduling represent a significant advancement in industrial production. His innovative patent showcases the potential of integrating deep learning and real-time monitoring to optimize production processes. Through his work, he continues to influence the future of personalized customized production.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
