An architecture of deep learning in QSPR modeling for the prediction of critical properties using molecular signatures-Reference-Cited by-同舟云学术

An architecture of deep learning in QSPR modeling for the prediction of critical properties using molecular signatures

Published:2019-06-18 Issue:9 Volume:65 Page:
ISSN:0001-1541
Container-title:AIChE Journal
language:en
Short-container-title:AIChE J

Author:

Su Yang¹,Wang Zihao¹,Jin Saimeng¹,Shen Weifeng¹,Ren Jingzheng²,Eden Mario R.³

Affiliation:

1. School of Chemistry and Chemical EngineeringChongqing University Chongqing China

2. Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hong Kong SAR China

3. Department of Chemical EngineeringAuburn University Auburn Alabama

Funder

National Natural Science Foundation of China

Chongqing Research Program of Basic Research and Frontier Technology

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aic.16678

Reference50 articles.

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3. Introduction to Computer Aided Property Estimation

4. LydersenAL. Estimation of critical properties of organic compounds. University of Wisconsin College of Engineering. Eng Exp Stn Rep. Madison: WI;1995.

5. Estimation of critical properties with group contribution methods

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