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Uncertainty

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Reinforcement-Learning-Based Disturbance Rejection Control for Uncertain Nonlinear Systems.

IEEE transactions on cybernetics
This article investigates the reinforcement-learning (RL)-based disturbance rejection control for uncertain nonlinear systems having nonsimple nominal models. An extended state observer (ESO) is first designed to estimate the system state and the tot...

Time-Synchronized Control for Disturbed Systems.

IEEE transactions on cybernetics
Finite-time control is concerned with steering a system state to the origin before a certain settling-time limit, ignoring any consideration of when each state element converges relative to the others. In this article, a control problem called time-s...

A Bayesian deep learning method for freeway incident detection with uncertainty quantification.

Accident; analysis and prevention
Incident detection is fundamental for freeway management to reduce non-recurrent congestions and secondary incidents. Recently, machine learning technologies have made considerable progress in the incident detection field, but many still face challen...

Distance and similarity measures for normal wiggly dual hesitant fuzzy sets and their application in medical diagnosis.

Scientific reports
The normal wiggly dual hesitant fuzzy set (NWDHFS) is a modern mathematical tool that can be used to express the deep ideas of membership and non-membership information hidden in the thought-level of decision-makers (DMs). To enhance and expand the a...

iCVM: An Interpretable Deep Learning Model for CVM Assessment Under Label Uncertainty.

IEEE journal of biomedical and health informatics
The Cervical Vertebral Maturation (CVM) method aims to determine the craniofacial skeletal maturational stage, which is crucial for orthodontic and orthopedic treatment. In this paper, we explore the potential of deep learning for automatic CVM asses...

Estimation and uncertainty analysis of groundwater quality parameters in a coastal aquifer under seawater intrusion: a comparative study of deep learning and classic machine learning methods.

Environmental science and pollution research international
Excessive withdrawal of groundwater for agricultural irrigation can cause seawater intrusion into coastal aquifers. Such a case will in turn results in deterioration of irrigation water quality. Determination of irrigation water quality with traditio...

A novel multichannel deep learning model for fast denoising of Monte Carlo dose calculations: preclinical applications.

Physics in medicine and biology
In preclinical radiotherapy with kilovolt (kV) x-ray beams, accurate treatment planning is needed to improve the translation potential to clinical trials. Monte Carlo based radiation transport simulations are the gold standard to calculate the absorb...

Motion Planning and Adaptive Neural Tracking Control of an Uncertain Two-Link Rigid-Flexible Manipulator With Vibration Amplitude Constraint.

IEEE transactions on neural networks and learning systems
This article deals with an uncertain two-link rigid-flexible manipulator with vibration amplitude constraint, intending to achieve its position control via motion planning and adaptive tracking approach. In motion planning, the motion trajectories fo...

Reacting and responding to rare, uncertain and unprecedented events.

Ergonomics
This work examines how we may be able to anticipate, respond to, and train for the occurrence of rare, uncertain, and unexpected events in human-machine systems operations. In particular, it uses a foundational matrix which describes the combinations...

SCORCH: Improving structure-based virtual screening with machine learning classifiers, data augmentation, and uncertainty estimation.

Journal of advanced research
INTRODUCTION: The discovery of a new drug is a costly and lengthy endeavour. The computational prediction of which small molecules can bind to a protein target can accelerate this process if the predictions are fast and accurate enough. Recent machin...