Evidence map›Paper›PMID 34840559›Full record

ArticleComputational intelligence and neuroscience2021

Research on Practical Intelligent Mode of Digital Image Economy Based on Improved Genetic Multilayer Neural Network.

Min Guo, Liying Song, Muhammad Ilyas

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2021. 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
–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

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.

Min GuoSchool of Economics and Finance, Xi'an Jiaotong University, Xian, Shaanxi 710061, China.ORCID https://orcid.org/0000-0002-8771-7674
Liying SongSchool of Economics and Finance, Xi'an Jiaotong University, Xian, Shaanxi 710061, China.ORCID https://orcid.org/0000-0002-9860-2602
Muhammad IlyasSchool of Economics and Finance, Xi'an Jiaotong University, Xian, Shaanxi 710061, China.ORCID https://orcid.org/0000-0002-3927-651X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of economic globalization and digitization, the current financial field is in an unprecedented complex situation. The methods and means to deal with this complexity are developing towards image intelligence. This paper takes financial prediction as the starting point, selects the artificial neural network in the intelligent algorithm and optimizes the algorithm, forecasts through the improved multilayer neural network, and compares it with the traditional neural network. Through comparison, it is found that the prediction success rate of the improved genetic multilayer neural network increases with the increase of the dimension of the input image data. This shows that, by adding more technical indicators as the input of the combined network, the prediction efficiency of the improved genetic multilayer neural network can be further improved and the advantage of computing speed can be maintained.

Indexed as

Artificial IntelligenceNeural Networks, ComputerAlgorithmsForecastingIntelligence

Identifiers

PMID34840559
PMCPMC8626191

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.