公开(公告)号：US20230281474A1

公开(公告)日：2023-09-07

申请号：US17999515

申请日：2021-05-20

Applicant: BASF COATINGS GMBH

Inventor： Bernhard STEINMETZ ,  Michael BRUENNEMANN

IPC: G06N5/022

CPC classification number: G06N5/022

Abstract: Disclosed herein is a computer-implemented method for training a data-driven model for predicting properties of a chemical mixture. The method includes the steps of obtaining data including history and/or calibration data of a plurality of chemical mixture recipes and properties of each chemical mixture recipe, with each chemical mixture recipe including two or more ingredients, assigning at least one ingredient in each chemical mixture recipe to one of pre-defined substance clusters, each pre-defined substance cluster representing one ingredient or a group of ingredients having similar chemistry, revising each chemical mixture recipe by replacing the at least one ingredient with the assigned pre-defined substance cluster, and providing the revised chemical mixture recipes, together with the properties of the chemical mixture recipes, to a machine learning process in order to train a data-driven model, which is usable for predicting characteristics of properties of a new chemical mixture.