Evidence map›Paper›PMID 36210979›Full record

ArticleComputational intelligence and neuroscience2022

Systematic Risk Analysis of Semiconductor Global Market Based on Deep Feature Fusion K-Means Algorithm.

Wenjie Qiu

RetractedAbstract readRetracted Publication
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. It has been retracted, and should not be counted. 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

5 · Who and what money

Authors and funding

1 author.

Wenjie QiuGraduate School, Keimyung University, Deagu 42601, Republic of Korea.ORCID https://orcid.org/0000-0002-3861-5524

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the global semiconductor industry has entered a new round of rapid growth, it has also entered a golden cycle of economic growth. Semiconductor companies increase their intrinsic value through financing, industry mergers and acquisitions, and venture capital searches. At the same time, market investors pay more attention to the intrinsic value of companies when looking for good investment targets. Therefore, the systematic risk assessment of the global semiconductor market has become a common concern of market investors and corporate management. In this context, this paper found a method that can assess the systemic risk of the semiconductor global market, which is to use the K-means algorithm based on deep feature fusion. This paper analyzed the algorithm in depth, analyzed the quantum space of tensors, and used the definition of cluster fusion to obtain the relationship between the projection matrices

Indexed as

InvestmentsMarketingAlgorithmsRisk AssessmentSemiconductors

Identifiers

PMID36210979
PMCPMC9536936

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.