AIMC Topic: Computer Simulation

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Using recurrent neural network to estimate irreducible stochasticity in human choice behavior.

eLife
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others. In the current study, w...

GFANC-RL: Reinforcement Learning-based Generative Fixed-filter Active Noise Control.

Neural networks : the official journal of the International Neural Network Society
The recent Generative Fixed-filter Active Noise Control (GFANC) method achieves a good trade-off between noise reduction performance and system stability. However, labelling noise data for training the Convolutional Neural Network (CNN) in GFANC is t...

Complete synchronization of discrete-time fractional-order BAM neural networks with leakage and discrete delays.

Neural networks : the official journal of the International Neural Network Society
This paper concerns complete synchronization (CS) problem of discrete-time fractional-order BAM neural networks (BAMNNs) with leakage and discrete delays. Firstly, on the basis of Caputo fractional difference theory and nabla l-Laplace transform, two...

A Physics-Informed Neural Network approach for compartmental epidemiological models.

PLoS computational biology
Compartmental models provide simple and efficient tools to analyze the relevant transmission processes during an outbreak, to produce short-term forecasts or transmission scenarios, and to assess the impact of vaccination campaigns. However, their ca...

Mathematical modeling and numerical simulation of supercritical processing of drug nanoparticles optimization for green processing: AI analysis.

PloS one
In recent decades, unfavorable solubility of novel therapeutic agents is considered as an important challenge in pharmaceutical industry. Supercritical carbon dioxide (SCCO2) is known as a green, cost-effective, high-performance, and promising solven...

Time-optimal open-loop set stabilization of Boolean control networks.

Neural networks : the official journal of the International Neural Network Society
We show that for stabilization of Boolean control networks (BCNs) with unobservable initial states, open-loop control and close-loop control are not equivalent. An example is given to illustrate the nonequivalence. Enlightened by the nonequivalence, ...

State transition learning with limited data for safe control of switched nonlinear systems.

Neural networks : the official journal of the International Neural Network Society
Switching dynamics are prevalent in real-world systems, arising from either intrinsic changes or responses to external influences, which can be appropriately modeled by switched systems. Control synthesis for switched systems, especially integrating ...

Fish-inspired tracking of underwater turbulent plumes.

Bioinspiration & biomimetics
Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of...

Deep learning for contour quality assurance for RTOG 0933: In-silico evaluation.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To validate a CT-based deep learning (DL) hippocampal segmentation model trained on a single-institutional dataset and explore its utility for multi-institutional contour quality assurance (QA).

Deep active learning with high structural discriminability for molecular mutagenicity prediction.

Communications biology
The assessment of mutagenicity is essential in drug discovery, as it may lead to cancer and germ cells damage. Although in silico methods have been proposed for mutagenicity prediction, their performance is hindered by the scarcity of labeled molecul...