NDLI: A new estimation algorithm of physical properties based on a group contribution and support vector machine

Content Provider	Springer Nature Link
Author	Lee, Chang Jun Lee, Gibaek So, Won Yoon, En Sup
Copyright Year	2008
Abstract	There are two ways to evaluate the properties of unknown chemical compounds. One is by traditional approaches, which measure the desired data from the experiments and the other is by predicting them in the theoretical approaches using a kind of prediction model. The latter are considered to be more effective because they are less time consuming and cost efficient, and there is less risk in conducting the experiments. Besides, it is inconvenient to conduct experiments to obtain experimental data, especially for new materials or high molecular substances. Several methods using regression model and neural network for predicting the physical properties have been suggested so far. However, the existing methods have many problems in terms of accuracy and applicability. Therefore, an improved method for predicting the properties is needed. A new method for predicting the physical property was proposed to predict 15 physical properties for the chemicals which consist of C, H, N, O, S and Halogens. This method was based on the group contribution method that was oriented from the assumption that each fragment of a molecule contributes a certain amount to the value of its physical property. In order to improve the accuracy of the prediction of the physical properties and the applicability, we extended the database, significantly modifying the existing group contribution methods, and then established a new method for predicting the physical properties using support vector machine (SVM) which is a statistical theory that has never been used for predicting the physical properties. The SVM-based approach can develop nonlinear structure property correlations more accurately and easily in comparison with other conventional approaches. The results from the new estimation method are found to be more reliable, accurate and applicable. The newly proposed method can play a crucial role in the estimation of new compounds in terms of the expense and time.
Starting Page	568
Ending Page	574
Page Count	7
File Format	PDF
ISSN	02561115
Journal	Korean Journal of Chemical Engineering
Volume Number	25
Issue Number	3
e-ISSN	19757220
Language	English
Publisher	Springer US
Publisher Date	2008-07-02
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Group Contribution Method Functional Group Support Vector Machine Property Estimation Biotechnology Materials Science Catalysis Industrial Chemistry/Chemical Engineering
Content Type	Text
Resource Type	Article
Subject	Chemistry Chemical Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Flash point prediction of organic compounds using a group contribution and support vector machine

A group contribution method based on nonrandom lattice-hole theory with molecular bulkiness

Weighted support vector machine for quality estimation in polymerization processes

Melting-Point Estimation of Ionic Liquids by a Group Contribution Method

Composite group vector space method for estimating melting and boiling point of pure organic compound

An extension of the group contribution model for thermodynamic and transport properties of dilute gases

An extension of the group contribution method for estimating thermodynamic and transport properties. Part III. Noble gases

Olefin-Copper(I) Complexes and their Properties

New Group-Contribution Method for Predicting Temperature-Dependent Properties of Pure Organic Compounds

A new estimation algorithm of physical properties based on a group contribution and support vector machine

Similar Documents

Flash point prediction of organic compounds using a group contribution and support vector machine

A group contribution method based on nonrandom lattice-hole theory with molecular bulkiness

Weighted support vector machine for quality estimation in polymerization processes

Melting-Point Estimation of Ionic Liquids by a Group Contribution Method

Composite group vector space method for estimating melting and boiling point of pure organic compound

An extension of the group contribution model for thermodynamic and transport properties of dilute gases

An extension of the group contribution method for estimating thermodynamic and transport properties. Part III. Noble gases

Olefin-Copper(I) Complexes and their Properties

New Group-Contribution Method for Predicting Temperature-Dependent Properties of Pure Organic Compounds

A new estimation algorithm of physical properties based on a group contribution and support vector machine