Results 101 to 110 of about 2,032,077 (205)

An Explainable Bayesian TimesNet for Probabilistic Groundwater Level Prediction

Water Resources Research
Reliable groundwater level (GWL) prediction is essential for sustainable water resources management. Despite recent advances in machine learning (ML) methods for GWL prediction, further improvements may be made in uncertainty quantification and model ...
Zechen Peng, Shaoxing Mo, Alexander Y. Sun, Jichun Wu, Xiankui Zeng, Miao Lu, Xiaoqing Shi   +6 more
doaj   +1 more source

Probabilistic prediction of increased intracranial pressure in patients with severe traumatic brain injury. [PDF]

Sci Rep, 2022
Wijayatunga P, Koskinen LD, Sundström N.   +2 more
europepmc   +1 more source

Probabilistic Deep Learning on Spheres for Weather/Climate Applications [PDF]

This work presents the application of a probabilistic approach to an already existing deep learning model for weather and climate prediction. Probabilistic deep learning allows to capture and address the uncertainties related to the data given as input ...
Haddad, Yann Yasser
core  

An interpretable probabilistic prediction algorithm for shield movement performance

Frontiers in Earth Science
Total thrust and torque are two key indicators of shield movement performance. Most existing data-driven machine learning studies focus on developing more accurate models for predicting total thrust and torque but overlook the interpretability of the ...
Yapeng Zhang, Yapeng Zhang, Long Liu, Long Liu, Jian Wu, Jian Wu, Shaoxiang Zeng, Shaoxiang Zeng, Jianquan Hu, Yuanqin Tao, Yuanqin Tao, Yong Huang, Yong Huang, Xuetao Zhou, Xuetao Zhou, Xu Liang   +15 more
doaj   +1 more source

Conformal Prediction under Probabilistic Input [PDF]

, 2014
In this paper we discuss a possible approach to confident prediction from data containing missing values presented in a probabilistic form. To achieve this we revise and generalize the notion of credibility known in the theory of conformal prediction.
openaire   +1 more source

Uncertainty estimation of machine learning spatial precipitation predictions from satellite data

Machine Learning: Science and Technology
Merging satellite and gauge data with machine learning produces high-resolution precipitation datasets, but uncertainty estimates are often missing. We addressed the gap of how to optimally provide such estimates by benchmarking six algorithms, mostly ...
Georgia Papacharalampous, Hristos Tyralis, Nikolaos Doulamis, Anastasios Doulamis   +3 more
doaj   +1 more source

Probabilistic indexing for case-based prediction

, 1997
The main assumption underlying case-based reasoning is that a problem with similar features as an earlier one is likely to have the same solution. However, this assumption has never been formally justified, and one can easily find practical situations where it is not true. We use probablity theory to show that even if this fundamental assumption can be
openaire   +3 more sources

Probabilistic long-term prediction for autonomous vehicles

, 2017
Long-term prediction of traffic participants is crucial to enable autonomous driving on public roads. The quality of the prediction directly affects the frequency of trajectory planning.
Stefan Hoermann, Hörmann, Stefan, Klaus Dietmayer, Dietmayer, Klaus, Daniel Stumper, Stumper, Daniel   +5 more
core   +1 more source

Comparing the performance of different neural networks architectures for the prediction of mineral prospectivity [PDF]

, 2005
In the mining industry, effective use of geographic information systems (CIS) to identify new geographic locations that are favorable for mineral exploration is very important. However, definitive prediction of such location is not an easy task.
Brown, W., Wong, K.W., Warick Brown, Fung, C.C., Iyer, V., Chun Che Fung, Vanaja Iyer, Kok Wai Wong   +7 more
core  

Hybrid Deep Learning‐Based Networks for Deterministic and Probabilistic Wind Nowcasting Within a Wake Vortex Warning System for Vertiport Operations

Meteorological Applications
Accurate wind prediction is essential for forecasting the transport and decay of wake vortices that might cause an adverse impact to light aircraft operations.
Sooseok Lee, Frank Holzäpfel, Anton Stephan, Dieter Moormann   +3 more
doaj   +1 more source