AIMC Topic: Time Factors

Clear Filters Showing 631 to 640 of 2001 articles

Broad Echo State Network with Reservoir Pruning for Nonstationary Time Series Prediction.

Computational intelligence and neuroscience
The nonstationary time series is generated in various natural and man-made systems, of which the prediction is vital for advanced control and management. The neural networks have been explored in the time series prediction, but the problem remains in...

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

Journal of healthcare engineering
This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its su...

Finite-time and sampled-data synchronization of complex dynamical networks subject to average dwell-time switching signal.

Neural networks : the official journal of the International Neural Network Society
This study deals with the finite-time synchronization problem of a class of switched complex dynamical networks (CDNs) with distributed coupling delays via sampled-data control. First, the dynamical model is studied with coupling delays in more detai...

A Graph Neural Network with Spatio-Temporal Attention for Multi-Sources Time Series Data: An Application to Frost Forecast.

Sensors (Basel, Switzerland)
Frost forecast is an important issue in climate research because of its economic impact on several industries. In this study, we propose GRAST-Frost, a graph neural network (GNN) with spatio-temporal architecture, which is used to predict minimum tem...

Automatic classification of nerve discharge rhythms based on sparse auto-encoder and time series feature.

BMC bioinformatics
BACKGROUND: Nerve discharge is the carrier of information transmission, which can reveal the basic rules of various nerve activities. Recognition of the nerve discharge rhythm is the key to correctly understand the dynamic behavior of the nervous sys...

Injection attack estimation of networked control systems subject to hidden DoS attack.

ISA transactions
This paper is concerned with the injection attack estimation for a class of networked control systems with Deny-of-Service (DoS) attack, where unknown signals are injected into the sensor reading and actuator. The main goal is to design an estimator ...

Factors associated with long-term survival in gemcitabine-concurrent proton radiotherapy for non-metastatic locally advanced pancreatic cancer: a single-center retrospective study.

Radiation oncology (London, England)
BACKGROUND: Factors associated with long-term survival in gemcitabine-concurrent proton radiotherapy (GPT) for non-metastatic, locally advanced pancreatic cancer (LAPC) remain unclear. This study aimed to determine the factors associated with long-te...

Synchronization issue of coupled neural networks based on flexible impulse control.

Neural networks : the official journal of the International Neural Network Society
The global exponential synchronization issue of coupled neural networks with time-delayed impulses is investigated in this paper. On the basis of the characteristics of coupled neural networks and theorems, we have built a novel coupled systems model...

A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG.

Scientific reports
Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This development has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The deman...

Dynamic Bayesian networks for prediction of health status and treatment effect in patients with chronic lymphocytic leukemia.

Scientific reports
Chronic lymphocytic leukemia (CLL) is the most common blood cancer in adults. The course of CLL and patients' response to treatment are varied. This variability makes it difficult to select the most appropriate treatment regimen and predict the progr...