AIMC Topic: Uncertainty

Clear Filters Showing 621 to 630 of 737 articles

Finite-time robust stabilization of uncertain delayed neural networks with discontinuous activations via delayed feedback control.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the finite-time robust stabilization of delayed neural networks (DNNs) in the presence of discontinuous activations and parameter uncertainties. By using the nonsmooth analysis and control theory, a delayed controller is ...

Predicting concrete corrosion of sewers using artificial neural network.

Water research
Corrosion is often a major failure mechanism for concrete sewers and under such circumstances the sewer service life is largely determined by the progression of microbially induced concrete corrosion. The modelling of sewer processes has become possi...

A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses.

Computational and mathematical methods in medicine
In medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the...

Matrix measure based dissipativity analysis for inertial delayed uncertain neural networks.

Neural networks : the official journal of the International Neural Network Society
The present paper is devoted to investigating the global dissipativity for inertial neural networks with time-varying delays and parameter uncertainties. By virtue of a suitable substitution, the original system is transformed to the first order diff...

Optimism in Active Learning.

Computational intelligence and neuroscience
Active learning is the problem of interactively constructing the training set used in classification in order to reduce its size. It would ideally successively add the instance-label pair that decreases the classification error most. However, the eff...

Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
The fixed-time master-slave synchronization of Cohen-Grossberg neural networks with parameter uncertainties and time-varying delays is investigated. Compared with finite-time synchronization where the convergence time relies on the initial synchroniz...

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

ISA transactions
This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to de...

Structure Identification of Uncertain Complex Networks Based on Anticipatory Projective Synchronization.

PloS one
This paper investigates a method to identify uncertain system parameters and unknown topological structure in general complex networks with or without time delay. A complex network, which has uncertain topology and unknown parameters, is designed as ...

New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays.

ISA transactions
In this paper, the problem of passivity analysis is studied for memristor-based uncertain neural networks with leakage and time-varying delays. By combining differential inclusions with set-valued maps, the system of memristive neural networks is cha...

Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences.

Artificial intelligence in medicine
OBJECTIVES: Inspired by real-world examples from the forensic medical sciences domain, we seek to determine whether a decision about an interventional action could be subject to amendments on the basis of some incomplete information within the model,...