Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Qun Tu"'
Publikováno v:
Tehnički Vjesnik, Vol 31, Iss 3, Pp 832-836 (2024)
With the rapid rise of online classrooms, monitoring student engagement is critical but challenging for educators. This work explores how artificial intelligence (AI) and big data techniques can automatically evaluate student concentration levels in
Externí odkaz:
https://doaj.org/article/e33d3d81eaed4c9395ce63a22989e4da
Publikováno v:
Tehnički Vjesnik, Vol 30, Iss 5, Pp 1585-1593 (2023)
An accurate and reliable forecasting method of the subway passenger flow provides the operators with more valuable reference to make decisions, especially in reducing energy consumption and controlling potential risks. However, due to the non-recurre
Externí odkaz:
https://doaj.org/article/07a3313e850341919650737e7a35229d
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 3, Pp 2459-2473 (2021)
Abstract An improved text classification method based on domain ontology is proposed in this paper to organize the mass information that records node enterprises’ innovation activities under the supply chain environment. This method can classify th
Externí odkaz:
https://doaj.org/article/8029a55be0c6493d83bd3455e5e8d5f6
Publikováno v:
IEEE Access, Vol 8, Pp 12354-12363 (2020)
The imperfection of the guide signs in the subway will lead to many difficulties for passengers, which directly affects the operation efficiency of subway stations. In this paper, we use big data to analyze the problem of signages in Beijing subway,
Externí odkaz:
https://doaj.org/article/0038cf922a094c01a9f1206ee4b111d4
Publikováno v:
IEEE Access, Vol 7, Pp 157353-157362 (2019)
With the development of railway transportation, the railway transportation enterprises expand their freight transportation from station-to-station transportation to door-to-door transportation, which makes the routing design more complicated. The exi
Externí odkaz:
https://doaj.org/article/04aecf6d49854fe5ba8b9bf4f5e36a05
Publikováno v:
IEEE Transactions on Fuzzy Systems. 31:394-406
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc31147e7f090498f8493020f5070a9a
https://doi.org/10.1109/tfuzz.2022.3179779
https://doi.org/10.1109/tfuzz.2022.3179779
Publikováno v:
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL. 18
Technological innovation is vital for the survival and development of enterprises. In the era of intelligent information interconnection and knowledge-driven economy, there is a growing interest in how to manage high-volume data, unlock its potential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cff6459a468a14be990c771ba9307fa5
https://doi.org/10.15837/ijccc.2023.2.5241
https://doi.org/10.15837/ijccc.2023.2.5241
Publikováno v:
Big Data.
Demand forecasting is one of the managers' concerns in service supply chain management. With accurate passenger flow forecasting, the station-level service suppliers can make better service plans accordingly. However, the existing forecasting model c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a6521ce2aa95a838c07ba17496dcf88
https://doi.org/10.1089/big.2021.0318
https://doi.org/10.1089/big.2021.0318
Autor:
Qun Tu1 17113133@bjtu.edu.cn, Qianqian Zhang1
Publikováno v:
Journal of Coastal Research. 2019 Special Issue1, Vol. 94, p50-54. 5p.
Publikováno v:
International Journal of Computers Communications & Control. 14:107-123
This paper proposed a method for building enterprise's technological innovation domain ontology automatically from plain text corpus based on Latent Dirichlet Allocation (LDA). The proposed method consisted of four modules: 1) introducing the seed on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e0f56b86b1952018f13af3ca8d9b73a
https://doi.org/10.15837/ijccc.2019.1.3366
https://doi.org/10.15837/ijccc.2019.1.3366