Results 51 to 60 of about 65,665 (164)

Interval reservoir computing: theory and case studies

Frontiers in Energy Research
The time series data in many applications, for example, wind power and vehicle trajectory, show significant uncertainty. Using a single prediction value of wind power as feedback information for wind turbine control or unit commitment is not enough since
Lan-Da Gao, Lan-Da Gao, Zhen-Hua Li, Zhen-Hua Li, Meng-Yi Wu, Meng-Yi Wu, Qing-Lan Fan, Qing-Lan Fan, Ling Xu, Ling Xu, Zhuo-Min Zhang, Zhuo-Min Zhang, Yi-Peng Zhang, Yi-Peng Zhang, Yan-Yue Liu, Yan-Yue Liu   +15 more
doaj   +1 more source

Leveraging sanitized data for probabilistic electricity market prediction: a Singapore case study

Frontiers in Energy Research, 2023
In deregulated electricity markets, predicting price and load is a common practice. However, market participants and shareholders often seek deeper insights into other system statuses associated with price prediction, such as power flow and market share ...
Ning Zhou Xu, Xiang Gao, Songjian Chai, Ming Niu, Jia Xin Yang   +4 more
doaj   +1 more source

Generative probabilistic prediction of precipitation induced landslide deformation with variational autoencoder and gated recurrent unit

Frontiers in Earth Science
Landslides, prevalent in mountainous areas, are typically triggered by tectonic movements, climatic changes, and human activities. They pose catastrophic risks, especially when occurring near settlements and infrastructure.
Wencheng Cai, Fuan Lan, Xianhao Huang, Junfeng Hao, Weifeng Xia, Ran Tang, Peng Feng, Huajin Li   +7 more
doaj   +1 more source

Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles With Federated Learning

IEEE Open Journal of Vehicular Technology, 2021
Today's drivers of battery electric vehicles must deal with limited driving range in a sparse charging infrastructure. An accurate prediction of energy demand and driving range is therefore important and enables reliable routing and charge ...
Adam Thor Thorgeirsson, Stefan Scheubner, Sebastian Funfgeld, Frank Gauterin   +3 more
doaj   +1 more source

Probabilistic Prediction in Scikit-Learn

, 2021
This research is partly funded by the Swedish Knowledge Foundation through the industrial graduate school INSIDR.
Sweidan, Dirar, Johansson, Ulf
openaire   +2 more sources

Comprehensive data aleatory uncertainty propagation in regression random forest using a Monte Carlo approach: a struggle with incomplete data provision using a case study on probabilistic soil moisture regionalization

Frontiers in Environmental Science
Data uncertainty never decreases along processing chains and should always be reported alongside processing results. In this study, we attempt to propagate aleatory data uncertainty through a multiple regression analysis to generate regionalized ...
Hendrik Paasche, Ségolène Dega, Martin Schrön, Peter Dietrich, Peter Dietrich   +4 more
doaj   +1 more source

Machine Learning Approaches for Probabilistic Prediction of Coastal Freak Waves

Journal of Marine Science and Engineering
Coastal freak waves (CFWs) are sudden and hazardous wave events that occur near shorelines and can pose serious threats to coastal visitors and infrastructure.
Dong-Jiing Doong, Wei-Cheng Chen, Fan-Ju Lin, Chi Pan, Cheng-Han Tsai   +4 more
doaj   +1 more source

Learning Adaptive Probabilistic Models for Uncertainty-Aware Air Pollution Prediction

IEEE Access, 2023
The air pollution problem has been a serious issue for public health and city development in recent years, which rises an urgent demand for accurate air pollution prediction models.
Zhiyuan Wu, Ning Liu, Guodong Li, Xinyu Liu, Yue Wang, Lin Zhang   +5 more
doaj   +1 more source

Probabilistic Prompt Learning for Dense Prediction

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Recent progress in deterministic prompt learning has become a promising alternative to various downstream vision tasks, enabling models to learn powerful visual representations with the help of pre-trained vision-language models. However, this approach results in limited performance for dense prediction tasks that require handling more complex and ...
Hyeongjun Kwon, Taeyong Song, Somi Jeong, Jin Kim 0005, Jinhyun Jang, Kwanghoon Sohn   +5 more
openaire   +2 more sources

Near‐term lake water temperature forecasts can be used to anticipate the ecological dynamics of freshwater species

Ecosphere
Near‐term ecological forecasting can be used to improve operational resource management in freshwater ecosystems. Here, we developed a framework that uses water temperature forecasting as a tool to predict the migrations of Atlantic salmon (Salmo salar ...
Ricardo Paíz, R. Quinn Thomas, Cayelan C. Carey, Elvira deEyto, Ian D. Jones, Austin D. Delany, Russell Poole, Pat Nixon, Mary Dillane, Valerie McCarthy, Suzanne Linnane, Eleanor Jennings   +11 more
doaj   +1 more source