Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Zhizhe Lin"'
Publikováno v:
Mathematics, Vol 12, Iss 20, p 3303 (2024)
Reliable forecasting of short-term traffic flow is an essential component of modern intelligent transport systems. However, existing methods fail to deal with the non-linear nature of short-term traffic flow, often making the forecasting unreliable.
Externí odkaz:
https://doaj.org/article/3e89e6cd6b3d4b5caf7d73f48cc67992
Publikováno v:
Mathematics, Vol 12, Iss 12, p 1895 (2024)
Nowadays, accurate and efficient short-term traffic flow forecasting plays a critical role in intelligent transportation systems (ITS). However, due to the fact that traffic flow is susceptible to factors such as weather and road conditions, traffic
Externí odkaz:
https://doaj.org/article/89cb955cf5704bf6b7e0ad59bd7ac38c
Autor:
Sifan Huang, Xinyu Wang, Mengmeng Liu, Zhizhe Lin, Wenqian Gu, Haili Zhao, Yanqiu Zhang, Baoyue Ding, Jiyong Liu, Xin Wu, Wei Fan, Jianming Chen
Publikováno v:
Drug Delivery, Vol 29, Iss 1, Pp 1132-1141 (2022)
Sodium aescinate (SA) is often used for intravenous (IV) injection owing to its anti-inflammatory, anti-exudative, increasing venous tension, improving blood circulation and reducing swelling activities. However, the clinical application of SA is lim
Externí odkaz:
https://doaj.org/article/6d05b00dd7a9468683e407ddf367ba5b
Publikováno v:
Mathematics, Vol 12, Iss 1, p 103 (2023)
Short-term traffic flow forecasting, an essential enabler for intelligent transportation systems, is a fundamental and challenging task for dramatically changing traffic flow over time. In this paper, we present a gravitational search optimized kerne
Externí odkaz:
https://doaj.org/article/2931f99891e642598692a118abdcae79
Publikováno v:
IEEE Access, Vol 10, Pp 123337-123348 (2022)
Passport security feature classification has always been an important issue in border checks. Current manual methods struggle to achieve satisfactory results in terms of consistency and stability for security features with high similarity. For this r
Externí odkaz:
https://doaj.org/article/3ae54e3a16174d029248cf6303828472
Autor:
Hang Chen, Sifan Huang, Heyi Wang, Xinmei Chen, Haiyan Zhang, Youfa Xu, Wei Fan, Yun Pan, Qiuyan Wen, Zhizhe Lin, Xuena Wang, Yongwei Gu, Baoyue Ding, Jianming Chen, Xin Wu
Publikováno v:
Drug Delivery, Vol 28, Iss 1, Pp 1067-1079 (2021)
Background Combination of the prodrug technique with an albumin nano drug-loaded system is a novel promising approach for cancer treatment. However, the long-lasting and far-reaching challenge for the treatment of cancers lies in how to construct the
Externí odkaz:
https://doaj.org/article/871f919b5a5c4462a989f6c80f144b1c
Publikováno v:
Mathematics, Vol 10, Iss 15, p 2772 (2022)
It is significant for anesthesiologists to have a precise grasp of the recovery time of the patient after anesthesia. Accurate prediction of anesthesia recovery time can support anesthesiologist decision-making during surgery to help reduce the risk
Externí odkaz:
https://doaj.org/article/e26733972f12446ca14d6393afe95868
Publikováno v:
Complexity, Vol 2021 (2021)
Accurate short-term traffic flow modeling is an essential prerequisite to analyze and control traffic flow. Canonical data-driven methods are a large account of parameters that may be underfitted with limited training samples, yet they cannot adaptiv
Externí odkaz:
https://doaj.org/article/17158f20e2d04da0a1c81f5159cd7458
Publikováno v:
Engineering Applications of Artificial Intelligence. 123:106411
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cad8267789dd369a82fed00eea76d98b
https://doi.org/10.1016/j.engappai.2023.106411
https://doi.org/10.1016/j.engappai.2023.106411
Publikováno v:
Journal of drug targeting. 31(1)
Nanomedicine offers considerable opportunities to improve drugability and reduce toxicity for tumour therapy. However, the application of nanomedicine has achieved little success in clinical trials due to multiple physiological barriers to drug deliv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e404137a33acdeaf119fd047e4a822e5
https://pubmed.ncbi.nlm.nih.gov/35857432
https://pubmed.ncbi.nlm.nih.gov/35857432