公开(公告)号：US20230186254A1

公开(公告)日：2023-06-15

申请号：US17984514

申请日：2022-11-10

Applicant: Tianjin University of Commerce

Inventor： Guanyi CHEN ,  Chengming DU ,  Yunan SUN ,  Junyu TAO ,  Xinyi LIU ,  Lan MU ,  Xiaohua WANG ,  Zhenyu WANG ,  Yanni ZHENG

IPC: G06Q10/00 ,  B09B3/40 ,  G06N5/02

CPC classification number: G06Q10/30 ,  B09B3/40 ,  G06N5/022 ,  B09B2101/25

Abstract: Disclosed is an optimizing method for multi-source municipal solid waste combinations based on machine learning, including obtaining relevant property data, classifying the feature variables and obtaining a raw materials pre-combination from the classified feature variables according to a classification ratio, followed by cooperative combustion treatment to obtain data after combustion, summarizing the obtained data into a database, constructing a matrix of raw material components, operating conditions and pollutant distribution according to the database, obtaining matrix data; performing principal component analysis on the matrix data, constructing an information processing model, obtaining a data set of samples; carrying out training according to the data set to construct a relational model, obtaining processed parameters; training the obtained processed parameters to construct a regression module, an optimal parameter, and performing regression calculation using the optimal parameter together with the matrix data to obtain an optimization scheme of solid waste raw materials combinations.