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Energy-Based Open-World Uncertainty Modeling for Confidence Calibration [PDF]
Confidence calibration is of great importance to the reliability of decisions made by machine learning systems. However, discriminative classifiers based on deep neural networks are often criticized for producing overconfident predictions that fail to ...
Yezhen Wang +5 more
semanticscholar +1 more source
Gait Event Prediction Using Surface Electromyography in Parkinsonian Patients
Gait disturbances are common manifestations of Parkinson’s disease (PD), with unmet therapeutic needs. Inertial measurement units (IMUs) are capable of monitoring gait, but they lack neurophysiological information that may be crucial for studying gait ...
Stefan Haufe +3 more
doaj +1 more source
Reliability-based Probabilistic Wind Power Planning Considering Correlation of Load and Wind [PDF]
Wind power has been considered a future alternative to fossil energy resources. However, due to its stochastic nature, the integration of wind power plants (WPPs) into power systems poses some reliability problems such as a mismatch between load profile ...
Morteza Jadidoleslam +1 more
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Review of Uncertainty Modeling for Optimal Operation of Integrated Energy System
The operation of the integrated energy system will be affected by uncertainties, leading to sub-optimal design decisions. Accurate and effective modeling of these uncertainties is essential to ensure the optimal integration of renewable energy in the ...
H. Fan +3 more
semanticscholar +1 more source
Uncertainty Modeling with Second-Order Transformer for Group Re-identification
Group re-identification (G-ReID) focuses on associating the group images containing the same persons under different cameras. The key challenge of G-ReID is that all the cases of the intra-group member and layout variations are hard to exhaust.
Quan Zhang +3 more
semanticscholar +1 more source
Large-scale integration of wind power generation decreases the equivalent inertia of a power system, and thus makes frequency stability control challenging.
Cheng Yan +4 more
semanticscholar +1 more source
Modeling Model Uncertainty [PDF]
Recently there has been a great deal of interest in studying monetary policy under model uncertainty. We develop new methods to analyze different sources of uncertainty in one coherent structure, which is useful for policy decisions. We show how to estimate the size of the uncertainty based on time series data, and how to incorporate this uncertainty ...
Onatski, Alexei, Williams, Noah
openaire +5 more sources
A New Stochastic Model for Bus Rapid Transit Scheduling with Uncertainty
Nowadays, authorities of large cities in the world implement bus rapid transit (BRT) services to alleviate traffic problems caused by the significant development of urban areas.
Milad Dehghani Filabadi +4 more
doaj +1 more source
Nested Models and Model Uncertainty [PDF]
AbstractUncertainty about the appropriate choice among nested models is a concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space, ignoring the special status of submodels (e.g., those resulting from zero restrictions).
Kriwoluzky, A., Stoltenberg, C.A.
openaire +7 more sources
Multi-energy systems (MES) allow various energy forms, such as electricity, gas, and heat, to interact and achieve energy transfer and mutually benefit, reducing the probability of load cutting in the event of a failure, increasing the energy utilization
Ziyan Liao, Alessandra Parisio
doaj +1 more source

