The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 06, 2025
Filed:
Jul. 22, 2024
Chinese Research Academy of Environmental Sciences, Beijing, CN;
Shenzhen Qianhai Qiming Technology Co., Ltd., Shenzhen, CN;
Wei Tang, Beijing, CN;
Yang Li, Beijing, CN;
Jian Gao, Beijing, CN;
Zhongzhi Zhang, Beijing, CN;
Xiaohui Du, Beijing, CN;
Yang Yu, Beijing, CN;
Xuezhi Dai, Beijing, CN;
Jun Xu, Beijing, CN;
Shijie Liu, Beijing, CN;
Miaomiao Cheng, Beijing, CN;
Yunlang Wang, Beijing, CN;
Dazhi Wu, Shenzhen, CN;
CHINESE RESEARCH ACADEMY OF ENVIRONMENTAL SCIENCES, Beijing, CN;
SHENZHEN QIANHAI QIMING TECHNOLOGY CO., LTD., Shenzhen, CN;
Abstract
The present disclosure provides an inversion method for determining a pollution source list based on artificial intelligence and big data, an inversion system for determining the pollution source list based on artificial intelligence and big data, and applications thereof, which provides basic data support for government sectors to formulate relevant environmental protection measures. The specific technical solution employed in the present disclosure is as follows: finding out an emission source that makes the highest contribution to the pollutant concentration of any cell with an advanced 3D CNN artificial intelligence algorithm based on artificial intelligence and big data, establishing a model of the relationship between pollutant concentration and emission, and finding out the relationship between pollutant concentration and emission with machine learning technology, i.e., estimating an emission from a given pollutant concentration, and estimating a pollutant concentration from a given emission.