AIMC Topic: Uncertainty

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Uncertainty maximization in partially observable domains: A cognitive perspective.

Neural networks : the official journal of the International Neural Network Society
Faced with an ever-increasing complexity of their domains of application, artificial learning agents are now able to scale up in their ability to process an overwhelming amount of data. However, this comes at the cost of encoding and processing an in...

Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS.

PloS one
For many different types of businesses, additive manufacturing has great potential for new product and process development in many different types of businesses including automotive industry. On the other hand, there are a variety of additive manufac...

Bounded synchronization for uncertain master-slave neural networks: An adaptive impulsive control approach.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the bounded synchronization of the discrete-time master-slave neural networks (MSNNs) with uncertainty. To deal with the unknown parameter in the MSNNs, a parameter adaptive law combined with the impulsive mechanism is propose...

Uncertainty-driven dynamics for active learning of interatomic potentials.

Nature computational science
Machine learning (ML) models, if trained to data sets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse data sets. In this approach, th...

A general framework for robust stability analysis of neural networks with discrete time delays.

Neural networks : the official journal of the International Neural Network Society
Robust stability of different types of dynamical neural network models including time delay parameters have been extensively studied, and many different sets of sufficient conditions ensuring robust stability of these types of dynamical neural networ...

Dynamic risk assessment of hospital oxygen supply system by HAZOP and intuitionistic fuzzy.

PloS one
Events such as oxygen leakage in the oxygen generation systems can have severe consequences, such as fire and explosion. In addition, the disruption in the oxygenation systems can lead to a threat to patients' lives. Thus, this study aimed to identif...

Neural stochastic differential equations network as uncertainty quantification method for EEG source localization.

Biomedical physics & engineering express
EEG source localization remains a challenging problem given the uncertain conductivity values of the volume conductor models (VCMs). As uncertain conductivities vary across people, they may considerably impact the forward and inverse solutions of the...

Multivalued neutrosophic power partitioned Hamy mean operators and their application in MAGDM.

PloS one
The novel multivalued neutrosophic aggregation operators are proposed in this paper to handle the complicated decision-making situations with correlation between specific information and partitioned parameters at the same time, which are based on wei...

Medical multivariate time series imputation and forecasting based on a recurrent conditional Wasserstein GAN and attention.

Journal of biomedical informatics
OBJECTIVE: In the fields of medical care and research as well as hospital management, time series are an important part of the overall data basis. To ensure high quality standards and enable suitable decisions, tools for precise and generic imputatio...

Neural network model for imprecise regression with interval dependent variables.

Neural networks : the official journal of the International Neural Network Society
This paper presents a computationally feasible method to compute rigorous bounds on the interval-generalization of regression analysis to account for epistemic uncertainty in the output variables. The new iterative method uses machine learning algori...