Evidence map›Paper›PMID 36686936›Full record

ArticleRSC advances2023

Predicting the high heating value and nitrogen content of torrefied biomass using a support vector machine optimized by a sparrow search algorithm.

Liu Xiaorui, Yang Jiamin, Yuan Longji

Abstract read
In one paragraph

Article in RSC advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Liu XiaoruiSchool of Mine, China University of Mining and Technology 221116 Xuzhou China liuxiaorui214@cumt.edu.cn.ORCID https://orcid.org/0000-0002-5056-8628
Yang JiaminSchool of Mine, China University of Mining and Technology 221116 Xuzhou China liuxiaorui214@cumt.edu.cn.
Yuan LongjiSchool of Low-Carbon Energy and Power Engineering, China University of Mining and Technology 221116 Xuzhou China yuanlongji@cumt.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A support vector machine (SVM) model with RBF kernel function combined with sparrow search algorithm (SSA) optimization was developed to predict the HHV and nitrogen content (No) values of torrefied biomass based on the feedstock properties and torrefaction conditions. Results showed that SSA optimization significantly improved the prediction performance of the SVM model for both HHV and No. A coefficient of determination (

Identifiers

PMID36686936
PMCPMC9809988

What OpenQuestion holds

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LicenceCC BY-NC
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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.