Evidence map›Paper›PMID 36297860›Full record

ArticlePolymers2022

Prediction of Plasticizer Property Based on an Improved Genetic Algorithm.

Yuyin Zhang, Ningjie Deng, Shiding Zhang, Pingping Liu, Changjing Chen, Ziheng Cui, Biqiang Chen, Tianwei Tan

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 68% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Yuyin ZhangNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Ningjie DengNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Shiding ZhangNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Pingping LiuNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Changjing ChenNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Ziheng CuiNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.ORCID 0000-0002-8852-8330
Biqiang ChenNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Tianwei TanNational Energy R&D Center for Biorefinery, Beijing University of Chemical Technology, Beijing 100029, China.
Beijing University of Chemical Technology · CN

Funding

National Key Research and Development Project 2019YFB1504002National Natural Science Foundation of China 21706006
6 · The paper itself

Abstract

Different plasticizers have obvious differences in plasticizing properties. As one of the important indicators for evaluating plasticization performance, the substitution factor (SF) has great significance for product cost accounting. In this research, a genetic algorithm with "variable mutation probability" was developed to screen the key molecular descriptors of plasticizers that are highly correlated with the SF, and a SF prediction model was established based on these filtered molecular descriptors. The results show that the improved genetic algorithm greatly improved the prediction accuracy in different regression models. The coefficient of determination (

Indexed as

genetic algorithmgrid search algorithmmachine learningplasticizersubstitution factor

Identifiers

PMID36297860
PMCPMC9607559
OpenAlexW4304775597

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.