AIMC Topic: Time Factors

Clear Filters Showing 541 to 550 of 2001 articles

Target Enclosing and Coverage Control for Quadrotors with Constraints and Time-Varying Delays: A Neural Adaptive Fault-Tolerant Formation Control Approach.

Sensors (Basel, Switzerland)
This paper investigates the problem of formation fault-tolerant control of multiple quadrotors (QRs) for a mobile sensing oriented application. The QRs subject to faults, input saturation and time-varying delays can be controlled to perform a target-...

A Hybrid Model Based on Improved Transformer and Graph Convolutional Network for COVID-19 Forecasting.

International journal of environmental research and public health
The coronavirus disease 2019 (COVID-19) has spread rapidly around the world since 2020, with a significant fatality rate. Until recently, numerous countries were unable to adequately control the pandemic. As a result, COVID-19 trend prediction has be...

MTEDS: Multivariant Time Series-Based Encoder-Decoder System for Anomaly Detection.

Computational intelligence and neuroscience
Intrusion detection systems examine the computer or network for potential security vulnerabilities. Time series data is real-valued. The nature of the data influences the type of anomaly detection. As a result, network anomalies are operations that d...

New Criteria for Synchronization of Multilayer Neural Networks via Aperiodically Intermittent Control.

Computational intelligence and neuroscience
In this paper, the globally asymptotic synchronization of multi-layer neural networks is studied via aperiodically intermittent control. Due to the property of intermittent control, it is very hard to deal with the effect of time-varying delays and a...

Time series (re)sampling using Generative Adversarial Networks.

Neural networks : the official journal of the International Neural Network Society
We propose a novel bootstrap procedure for time series data based on Generative Adversarial networks (GANs). We show that the dynamics of common stationary time series processes can be learned by GANs and demonstrate that GANs trained on a single sam...

Developing a hybrid time-series artificial intelligence model to forecast energy use in buildings.

Scientific reports
The development of a reliable energy use prediction model is still difficult due to the inherent complex pattern of energy use data. There are few studies developing a prediction model for the one-day-ahead energy use prediction in buildings and opti...

Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks.

IEEE transactions on cybernetics
In this article, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may su...

Robust Sampled-Data Control for Switched Complex Dynamical Networks With Actuators Saturation.

IEEE transactions on cybernetics
In this article, an aperiodic sampled-data control problem is investigated for polytopic uncertain switched complex dynamical networks subject to actuator saturation. Due to the constraint on the upper bound of the sampling interval being no greater ...

Radar Target Detection Algorithm Using Convolutional Neural Network to Process Graphically Expressed Range Time Series Signals.

Sensors (Basel, Switzerland)
Under the condition of low signal-to-noise ratio, the target detection performance of radar decreases, which seriously affects the tracking and recognition for the long-range small targets. To solve it, this paper proposes a target detection algorith...

Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: Treatment of acute ischemic stroke is heavily contingent upon time, as there is a strong relationship between time clock and tissue progression. Work has established imaging biomarker assessments as surrogates for time since s...