Evidence map›Paper›PMID 35222635›Full record

ArticleComputational intelligence and neuroscience2022

Application of Distributed Probability Model in Sports Based on Deep Learning: Deep Belief Network (DL-DBN) Algorithm for Human Behaviour Analysis.

Tianyang Liu, Qizhe Zheng, Ling Tian

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 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
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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

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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.

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

3 authors.

Tianyang LiuPhysical Education Department, Guangzhou Sport University, Guangzhou 510500, Guangdong, China.ORCID https://orcid.org/0000-0002-1932-8917
Qizhe ZhengComputer Research Laboratory, South China University of Technology, Guangzhou 510641, Guangdong, China.
Ling TianPublic Physical Education Department, Guangzhou Maritime Institute, Guangzhou 510725, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increased development of information technology, almost all the sectors have been developed. Age, educational qualifications, gender, and other factors have no bearing on acquiring knowledge in information technology.Most humans use mobile phones and other gadgets to make their lives easier. Machine Learning techniques are used to analyse the given data and aid in the classification or prediction of the dataset depending on the problem statement. It is significant to determine human behaviour analysis in the context of sports. In this research, the Deep Learning-Deep Belief Network (DL-DBN) algorithm is implemented with probability to analyse human behaviour in sports and implement a distributed probability model for classifying the behavior. The classification results have shown that the accuracy for strength training is both the maximum and the smallest, reaching 99% and 71%, respectively.

Indexed as

Deep LearningAlgorithmsHumansMachine LearningProbability

Identifiers

PMID35222635
PMCPMC8881180

What OpenQuestion holds

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Registered trials

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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.