Construction of business innovation model for sports industry using a deep learning algorithm-Reference-Cited by-同舟云学术

Construction of business innovation model for sports industry using a deep learning algorithm

Published:2022-03-25 Issue:20 Volume:26 Page:10753-10763
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Lv Chenchen,Wang Yifeng,Ma Yin

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-022-06962-8.pdf

Reference24 articles.

1. Boakye KG, Prybutok VR, Ryan SD (2012) The intention of continued web-enabled phone service usage: a quality perspective. Oper Manag Res 5(1–2):14–24

2. Chen R (2020) Research on classification of cross-border e-commerce products based on image recognition and deep learning. IEEE Access 99:1–1

3. Chung TW (2009) A study on selections of strategic type of business in air-logistics industry clusters. Asian J Shipp Log 25(1):83–102

4. Dewhirst T, Sparks R (2003) Intertextuality, tobacco sponsorship of sports, and adolescent male smoking culture: a selective review of tobacco industry documents. J Sport Soc Issues 27(4):372–398

5. Fischer A, Igel C (2011) Bounding the bias of contrastive divergence learning. Neural Comput 23(3):664–673. https://doi.org/10.1162/NECO_a_00085

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise;PeerJ Computer Science;2024-02-29

2. Assessing key factors for sporting industry sustainable development through multilayer artificial perceptron neural network approach;Environmental Science and Pollution Research;2022-08-01

3. Editorial on decision support system for development of intelligent applications;Soft Computing;2022-07-29