AIMC Topic: Computer Simulation

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Multimode function multistability for Cohen-Grossberg neural networks with mixed time delays.

ISA transactions
In this paper, we are concerned with the multimode function multistability for Cohen-Grossberg neural networks (CGNNs) with mixed time delays. It is introduced the multimode function multistability as well as its specific mathematical expression, whi...

RBFNN Design Based on Modified Nearest Neighbor Clustering Algorithm for Path Tracking Control.

Sensors (Basel, Switzerland)
Radial basis function neural networks are a widely used type of artificial neural network. The number and centers of basis functions directly affect the accuracy and speed of radial basis function neural networks. Many studies use supervised learning...

Hybrid pointer networks for traveling salesman problems optimization.

PloS one
In this work, we proposed a hybrid pointer network (HPN), an end-to-end deep reinforcement learning architecture is provided to tackle the travelling salesman problem (TSP). HPN builds upon graph pointer networks, an extension of pointer networks wit...

Experiments in artificial culture: from noisy imitation to storytelling robots.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
This paper presents a series of experiments in collective social robotics, spanning more than 10 years, with the long-term aim of building embodied models of (aspects of) cultural evolution. Initial experiments demonstrated the emergence of behaviour...

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space.

Molecules (Basel, Switzerland)
Drug-induced liver injury (DILI) is a major concern for drug developers, regulators, and clinicians. However, there is no adequate model system to assess drug-associated DILI risk in humans. In the big data era, computational models are expected to p...

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Computational and mathematical methods in medicine
Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach...

Packet Flow Capacity Autonomous Operation Based on Reinforcement Learning.

Sensors (Basel, Switzerland)
As the dynamicity of the traffic increases, the need for self-network operation becomes more evident. One of the solutions that might bring cost savings to network operators is the dynamic capacity management of large packet flows, especially in the ...

Artificial neural network-based adaptive control for a DFIG-based WECS.

ISA transactions
This paper presents an artificial neural network-based adaptive control approach for a doubly-fed induction generator (DFIG) based wind energy conversion system (WECS). The control objectives are: (1) extraction of maximum available power from the wi...

Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction.

Journal of chemical information and modeling
We present results on the extent to which physics-based simulation (exemplified by FEP) and focused machine learning (exemplified by QuanSA) are complementary for ligand affinity prediction. For both methods, predictions of activity for LFA-1 inhibit...

Computed structures of core eukaryotic protein complexes.

Science (New York, N.Y.)
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coe...