Title:
AN ODOR PREDICTION METHOD FOR AQUEOUS POLYMER COMPOSITION
Document Type and Number:
WIPO Patent Application WO/2024/026672
Kind Code:
A1
Abstract:
A method and a system (400) for predicting odor of an aqueous polymer composition, such as a polymerising coating, comprising: analytically characterizing the aqueous polymer composition with a detector (4013), thereby generating concentration data for volatile organic compounds in the aqueous polymer composition from the analytical characterization; inputting the concentration data to a decision tree ensemble configured to predict an odor intensity of the aqueous polymer composition after polymerisation based on the concentration data; and outputting a predicted odor intensity of the aqueous polymer composition from the decision tree ensemble.
Inventors:
LYU HAN (CN)
MA YAN (CN)
SHI CHENYI (CN)
XU JIANMING (CN)
ZOU JIAN (CN)
JI ZHOUHUA (CN)
DEROCHER JONATHAN PAUL (US)
MA YAN (CN)
SHI CHENYI (CN)
XU JIANMING (CN)
ZOU JIAN (CN)
JI ZHOUHUA (CN)
DEROCHER JONATHAN PAUL (US)
Application Number:
PCT/CN2022/109691
Publication Date:
February 08, 2024
Filing Date:
August 02, 2022
Export Citation:
Assignee:
DOW GLOBAL TECHNOLOGIES LLC (US)
ROHM & HAAS (US)
DOW SILICONES CORP (US)
LYU HAN (CN)
MA YAN (CN)
SHI CHENYI (CN)
XU JIANMING (CN)
ZOU JIAN (CN)
JI ZHOUHUA (CN)
DEROCHER JONATHAN PAUL (US)
ROHM & HAAS (US)
DOW SILICONES CORP (US)
LYU HAN (CN)
MA YAN (CN)
SHI CHENYI (CN)
XU JIANMING (CN)
ZOU JIAN (CN)
JI ZHOUHUA (CN)
DEROCHER JONATHAN PAUL (US)
International Classes:
G01N33/00
Other References:
XU LING ET AL: "Composition and correlation of volatile organic compounds and odor emissions from typical indoor building materials based on headspace analysis", BUILDING AND ENVIRONMENT, vol. 221, 109321, 20 June 2022 (2022-06-20), pages 1 - 9, XP087120412, ISSN: 0360-1323, [retrieved on 20220620], DOI: 10.1016/J.BUILDENV.2022.109321
BYLINSKI HUBERT ET AL: "The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process", SUSTAINABILITY, vol. 11, no. 16, 15 August 2019 (2019-08-15), pages 1 - 12, XP093008864, DOI: 10.3390/su11164407
HSU YEN-CHIA ET AL: "Smell Pittsburgh : Engaging Community Citizen Science for Air Quality", ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS, vol. 10, no. 4, 32, 3 December 2020 (2020-12-03), 2 Penn Plaza, Suite 701 New York NY 10121-0701 USA, pages 1 - 49, XP093008754, ISSN: 2160-6455, DOI: 10.1145/3369397
PEDREGOSA, F. ET AL., JOURNAL OF MACHINE LEARNING RESEARCH, vol. 12, 2011, pages 2825 - 2830
CHEN, T.GUESTRIN, C.: "Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining", XGBOOST: A SCALABLE TREE BOOSTING SYSTEM, 2016, pages 785 - 794
BYLINSKI HUBERT ET AL: "The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process", SUSTAINABILITY, vol. 11, no. 16, 15 August 2019 (2019-08-15), pages 1 - 12, XP093008864, DOI: 10.3390/su11164407
HSU YEN-CHIA ET AL: "Smell Pittsburgh : Engaging Community Citizen Science for Air Quality", ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS, vol. 10, no. 4, 32, 3 December 2020 (2020-12-03), 2 Penn Plaza, Suite 701 New York NY 10121-0701 USA, pages 1 - 49, XP093008754, ISSN: 2160-6455, DOI: 10.1145/3369397
PEDREGOSA, F. ET AL., JOURNAL OF MACHINE LEARNING RESEARCH, vol. 12, 2011, pages 2825 - 2830
CHEN, T.GUESTRIN, C.: "Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining", XGBOOST: A SCALABLE TREE BOOSTING SYSTEM, 2016, pages 785 - 794
Attorney, Agent or Firm:
SHANGHAI PATENT & TRADEMARK LAW OFFICE, LLC (CN)
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