AIMC Topic: Computer Simulation

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Self-Learning Robust Control Synthesis and Trajectory Tracking of Uncertain Dynamics.

IEEE transactions on cybernetics
In this article, we investigate the self-learning robust control synthesis and tracking design of general uncertain dynamical systems. Based on the adaptive critic learning, the robust stabilization method is developed with the help of conducting pro...

Percolation in networks with local homeostatic plasticity.

Nature communications
Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportati...

Evaluation of shape factor impact on discharge coefficient of side orifices using boost simulation model with extreme learning machine data-driven.

Network (Bristol, England)
In this paper, for the first time, the impact of the shape factor on the discharge coefficient of side orifices is evaluated using the novel Extreme Learning Machine (ELM) model. In addition, the Monte Carlo simulations (MCs) are applied to assess th...

Research on Artificial Intelligence Classification and Statistical Methods of Financial Data in Smart Cities.

Computational intelligence and neuroscience
In order to improve the effect of financial data classification and extract effective information from financial data, this paper improves the data mining algorithm, uses linear combination of principal components to represent missing variables, and ...

Parametric Neural Network-Based Model Free Adaptive Tracking Control Method and Its Application to AFS/DYC System.

Computational intelligence and neuroscience
This paper deals with adaptive nonlinear identification and trajectory tracking problem for model free nonlinear systems via parametric neural network (PNN). Firstly, a more effective PNN identifier is developed to obtain the unknown system dynamics,...

Deep Learning-Assisted Repurposing of Plant Compounds for Treating Vascular Calcification: An In Silico Study with Experimental Validation.

Oxidative medicine and cellular longevity
BACKGROUND: Vascular calcification (VC) constitutes subclinical vascular burden and increases cardiovascular mortality. Effective therapeutics for VC remains to be procured. We aimed to use a deep learning-based strategy to screen and uncover plant c...

Re-evaluating Deep Neural Networks for Phylogeny Estimation: The Issue of Taxon Sampling.

Journal of computational biology : a journal of computational molecular cell biology
Deep neural networks (DNNs) have been recently proposed for quartet tree phylogeny estimation. Here, we present a study evaluating recently trained DNNs in comparison to a collection of standard phylogeny estimation methods on a heterogeneous collect...

Deep Unfolding for Non-Negative Matrix Factorization with Application to Mutational Signature Analysis.

Journal of computational biology : a journal of computational molecular cell biology
Non-negative matrix factorization (NMF) is a fundamental matrix decomposition technique that is used primarily for dimensionality reduction and is increasing in popularity in the biological domain. Although finding a unique NMF is generally not possi...

Exponential synchronization for variable-order fractional discontinuous complex dynamical networks with short memory via impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper considers the exponential synchronization issue for variable-order fractional complex dynamical networks (FCDNs) with short memory and derivative couplings via the impulsive control scheme, where dynamical nodes are modeled to be discontin...

Intelligent Fault Diagnosis Framework for Modular Multilevel Converters in HVDC Transmission.

Sensors (Basel, Switzerland)
Open circuit failure mode in insulated-gate bipolar transistors (IGBT) is one of the most common faults in modular multilevel converters (MMCs). Several techniques for MMC fault diagnosis based on threshold parameters have been proposed, but very few...