Zobrazeno 1 - 10
of 5 923
pro vyhledávání: '"Temporal data"'
Publikováno v:
Frontiers in Physiology, Vol 15 (2024)
Predictive modeling of clinical time series data is challenging due to various factors. One such difficulty is the existence of missing values, which leads to irregular data. Another challenge is capturing correlations across multiple dimensions in o
Externí odkaz:
https://doaj.org/article/469956f3adec4ea6964d30b8acbf16a3
Autor:
Yun WANG, Zhishuang DU, Kang TIAN, Xiaobao SU, Pengfei CHANG, Difei MEI, Jinyu LI, Longjian JI, Yifeng GUO, Wuai ZHOU, Wanzhe ZHANG, Jianhua FENG
Publikováno v:
大数据, Vol 10, Pp 149-160 (2024)
Natural resources and geographic information big data are regarded as essential productive factors in the context of digital government, and an important component of the national integrated government big data system.Due to data dispersion and isola
Externí odkaz:
https://doaj.org/article/62ef8302454f4d49b521c74499d81f9c
Publikováno v:
Human-Centric Intelligent Systems, Vol 4, Iss 3, Pp 406-416 (2024)
Abstract Government collaboration tasks are integral for grassroots governance and essential for government administration. Large-scale government collaboration tasks often involve multiple departments working together to solve complex tasks that req
Externí odkaz:
https://doaj.org/article/18e8c5ef817b4f69890ba417f795cba2
Autor:
Song Wu, Senliang Bao, Wei Dong, Senzhang Wang, Xiaojiang Zhang, Chengcheng Shao, Junxing Zhu, Xiaoyong Li
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Accurately predicting the spatio-temporal evolution trends and long-term dynamics of three-dimensional ocean temperature and salinity plays a crucial role in monitoring climate system changes and conducting fundamental oceanographic research. Numeric
Externí odkaz:
https://doaj.org/article/885c5c8386874a3f9d91f17601290480
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The traffic flow prediction is the key to alleviate traffic congestion, yet very challenging due to the complex influence factors. Currently, the most of deep learning models are designed to dig out the intricate dependency in continuous sta
Externí odkaz:
https://doaj.org/article/c2fe98e0cf8a4cbfb7834326bc536244
Autor:
HeounMo Go, SangHyun Park
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Crowd flow prediction has been studied for a variety of purposes, ranging from the private sector such as location selection of stores according to the characteristics of commercial districts and customer-tailored marketing to the public sec
Externí odkaz:
https://doaj.org/article/3b6a114c6e6f4af39687636bb95ce5e7
Publikováno v:
Geo-spatial Information Science, Pp 1-24 (2024)
The digital twin city technique maps the massive city environmental and social data on a three-dimensional virtual model. It presents the operational status of physical world and supports intelligent city governance. However, the inefficient utilizat
Externí odkaz:
https://doaj.org/article/bfe93bae2f174a1e895b7dc31407663e
Autor:
Abdulaziz Almaslukh, Aisha Almaalwy, Nasser Allheeib, Abdulaziz Alajaji, Mohammed Almukaynizi, Yazeed Alabdulkarim
Publikováno v:
PeerJ Computer Science, Vol 10, p e2297 (2024)
In recent years, social media has become much more popular to use to express people’s feelings in different forms. Social media such as X (i.e., Twitter) provides a huge amount of data to be analyzed by using sentiment analysis tools to examine the
Externí odkaz:
https://doaj.org/article/abceab3f25e14f7196c17b14c2c39dc7
Autor:
Lara Kassab, Alona Kryshchenko, Hanbaek Lyu, Denali Molitor, Deanna Needell, Elizaveta Rebrova, Jiahong Yuan
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 10 (2024)
Temporal text data, such as news articles or Twitter feeds, often comprises a mixture of long-lasting trends and transient topics. Effective topic modeling strategies should detect both types and clearly locate them in time. We first demonstrate that
Externí odkaz:
https://doaj.org/article/ee6b5308efdf457198bbdd709e663400