AIMC Topic: Uncertainty

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Rainfall prediction using multiple inclusive models and large climate indices.

Environmental science and pollution research international
Rainfall prediction is vital for the management of available water resources. Accordingly, this study used large lagged climate indices to predict rainfall in Iran's Sefidrood basin. A radial basis function neural network (RBFNN) and a multilayer per...

Observer-Based Fixed-Time Neural Control for a Class of Nonlinear Systems.

IEEE transactions on neural networks and learning systems
This article is concerned with an issue of fixed time adaptive neural control for a class of uncertain nonlinear systems subject to hysteresis input and immeasurable states. The state observer and neural networks (NNs) are used to estimate the immeas...

Handling Imbalanced Data: Uncertainty-Guided Virtual Adversarial Training With Batch Nuclear-Norm Optimization for Semi-Supervised Medical Image Classification.

IEEE journal of biomedical and health informatics
In manyclinical settings, a lot of medical image datasets suffer from imbalance problems, which makes predictions of trained models to be biased toward majority classes. Semi-supervised Learning (SSL) algorithms trained with such imbalanced datasets ...

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller.

Computational intelligence and neuroscience
The present study aims to design a robust adaptive controller employed in the active tuned mass damper (ATMD) system to overcome undesirable vibrations in multistory buildings under seismic excitations. We propose a novel adaptive type-2 neural-fuzzy...

DC Motor Control Technology Based on Multisensor Information Fusion.

Computational intelligence and neuroscience
To solve these uncertain problems by studying the motor fault diagnosis technology, so as to ensure the normal operation of the motor equipment is the primary problem to be solved in the field of motor fault diagnosis. The traditional DC motor is one...

Uncertainty Quantification for Deep Learning in Ultrasonic Crack Characterization.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Deep learning for nondestructive evaluation (NDE) has received a lot of attention in recent years for its potential ability to provide human level data analysis. However, little research into quantifying the uncertainty of its predictions has been do...

The Group Decision-Making Using Pythagorean Fuzzy Entropy and the Complex Proportional Assessment.

Sensors (Basel, Switzerland)
The Pythagorean fuzzy sets conveniently capture unreliable, ambiguous, and uncertain information, especially in problems involving multiple and opposing criteria. Pythagorean fuzzy sets are one of the popular generalizations of the intuitionistic fuz...

Effective Free-Driving Region Detection for Mobile Robots by Uncertainty Estimation Using RGB-D Data.

Sensors (Basel, Switzerland)
Accurate segmentation of drivable areas and road obstacles is critical for autonomous mobile robots to navigate safely in indoor and outdoor environments. With the fast advancement of deep learning, mobile robots may now perform autonomous navigation...

Self-normalized density map (SNDM) for counting microbiological objects.

Scientific reports
The statistical properties of the density map (DM) approach to counting microbiological objects on images are studied in detail. The DM is given by U[Formula: see text]-Net. Two statistical methods for deep neural networks are utilized: the bootstrap...

Using source data to aid and build variational state-space autoencoders with sparse target data for process monitoring.

Neural networks : the official journal of the International Neural Network Society
In industrial processes, different operating conditions and ratios of ingredients are used to produce multi-grade products in the same production line. Yet, the production grade changes so quickly as the demand from customers varies from time to time...