Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Hongshu Che"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8286-8296 (2023)
Precipitation nowcasting underlying various public services from rainstorm warning to flight safety is quite important and remains challenging due to the fast change in convective weather. Although some deep learning models have been proposed to make
Externí odkaz:
https://doaj.org/article/17674a71cb534dfdbb3476d841fb14c2
A Machine-Learning Approach Combining Wavelet Packet Denoising with Catboost for Weather Forecasting
Publikováno v:
Atmosphere, Vol 12, Iss 12, p 1618 (2021)
Accurate forecasting of future meteorological elements is critical and has profoundly affected human life in many aspects from rainstorm warning to flight safety. The conventional numerical weather prediction (NWP) sometimes leads to unsatisfactory p
Externí odkaz:
https://doaj.org/article/2459a7cf1196457388a8ac6a9932773c
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4285 (2021)
Precipitation nowcasting by radar echo extrapolation using machine learning algorithms is a field worthy of further study, since rainfall prediction is essential in work and life. Current methods of predicting the radar echo images need further impro
Externí odkaz:
https://doaj.org/article/91fc300347da4d7ead39ef8829b57cc5
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efd5fbcb566562ea6046c1ed95ac454d
https://doi.org/10.1109/lgrs.2022.3141498
https://doi.org/10.1109/lgrs.2022.3141498
Autor:
Hongshu Che, Yaokang Zhu, Pu Zhao, Yingnong Dang, Xu Zhang, Bo Qiao, Ze Li, Yong Xu, Qingwei Lin
Publikováno v:
2021 IEEE/ACM International Workshop on Cloud Intelligence (CloudIntelligence).
Large-scale cloud systems such as Microsoft Azure, Google Cloud and Amazon AWS provide a wide variety of online services which serve millions of customers around the world. Adverse service behaviors and latencies can have huge performance impact and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9258331caeaa589ca023650151aca0c3
https://doi.org/10.1109/cloudintelligence52565.2021.00016
https://doi.org/10.1109/cloudintelligence52565.2021.00016
Publikováno v:
SemEval@COLING
Natural Language Processing (NLP) has been widely used in the semantic analysis in recent years. Our paper mainly discusses a methodology to analyze the effect that context has on human perception of similar words, which is the third task of SemEval
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a10ecdc7d3b6a87892cef3f13339605
https://doi.org/10.18653/v1/2020.semeval-1.38
https://doi.org/10.18653/v1/2020.semeval-1.38
Publikováno v:
Remote Sensing, Vol 13, Iss 4285, p 4285 (2021)
Remote Sensing; Volume 13; Issue 21; Pages: 4285
Remote Sensing; Volume 13; Issue 21; Pages: 4285
Precipitation nowcasting by radar echo extrapolation using machine learning algorithms is a field worthy of further study, since rainfall prediction is essential in work and life. Current methods of predicting the radar echo images need further impro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de8b90a28f1e5c0597ccb75fb7093a46
https://doi.org/10.3390/rs13214285
https://doi.org/10.3390/rs13214285
Publikováno v:
Transportation Research Part C: Emerging Technologies. 124:102928
Short-term origin-destination (OD) flow prediction in urban rail transit (URT) plays a crucial role in smart and real-time URT operation and management. Different from other short-term traffic forecasting methods, the short-term OD flow prediction po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddecf3da594169076e2dc940f25e79a2
https://doi.org/10.1016/j.trc.2020.102928
https://doi.org/10.1016/j.trc.2020.102928
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11378 (2023)
With the increasing abundance of information resources and the development of deep learning techniques, recommender systems (RSs) based on deep learning have gradually become a research focus. Although RSs have evolved in recent years, a systematic r
Externí odkaz:
https://doaj.org/article/b98997af83e9423cb9969cf78ebb455d
Publikováno v:
IEEE Access, Vol 8, Pp 21282-21290 (2020)
Relationships between users in social networks have been widely used to improve recommender systems. However, actual social relationships are always sparse, which sometimes bring great harm to the performance of recommender systems. In fact, a user m
Externí odkaz:
https://doaj.org/article/29360d6c372f40a38b59efdd069abdd0