ArticleComputational intelligence and neuroscience2022
Application of Capital Asset Pricing Model Based on BP Neural Network in E-commerce Financing.
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 It has been retracted, and should not be counted.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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Retracted: Application of Capital Asset Pricing Model Based on BP Neural Network in E-commerce Financing.Computational intelligence and neuroscience · 2023Article
Corrections and comments
- Retraction · 2023-10-18Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/735FB3338ED467EB29D0BFC4B1ED69
- Retracted
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study explores the risks and benefits of investors in e-commerce financing under the background of "double carbon" to maximize investors' interests and reduce investment losses. The Back Propagation Neural Network (BPNN) algorithm model of e-commerce enterprise financing based on the Capital Asset Pricing Model (CAPM) is mainly studied. First, according to the worldwide literature, the theoretical concept and principle of the CAPM are deeply studied and analyzed. Then, from the perspective of "double carbon," with the financing risk characteristics of listed companies responding to the "double carbon" policy as samples, the CAPM model of e-commerce financing under the BPNN algorithm is established. Next, the BPNN is used to input the financing samples of e-commerce enterprises and train the model. The verification experiment of the capital asset financing model of e-commerce enterprises is further conducted. The experimental results show that the model error is the smallest when the number of neurons in the hidden layer reaches about 20. Therefore, the number of neurons in the hidden layer of the model is set to 20. When the number of iterations in training reaches 3000, the financing risk model begins to show a convergence trend. Finally, it can be determined that the number of adaptive iterations of the model is 3000. When the learning rate is 0.03, the oscillation of the model is smaller and stabler, so the model learning rate is 0.03, and the final model error is only 9.96 × 10
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.