AIMC Topic: Computer Simulation

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Metaheuristic Algorithms for Convolution Neural Network.

Computational intelligence and neuroscience
A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metah...

Reaction-diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality.

Physical review. E
Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic fee...

FDI based on Artificial Neural Network for Low-Voltage-Ride-Through in DFIG-based Wind Turbine.

ISA transactions
As per modern electrical grid rules, Wind Turbine needs to operate continually even in presence severe grid faults as Low Voltage Ride Through (LVRT). Hence, a new LVRT Fault Detection and Identification (FDI) procedure has been developed to take the...

Extended dissipative state estimation for memristive neural networks with time-varying delay.

ISA transactions
This paper investigates the problem of extended dissipative state estimation for memristor-based neural networks (MNNs) with time-varying delay. Based on both nonsmooth analysis and the construction of a new Lyapunov-Krasovskii functional, the extend...

Development of a Support Vector Machine-Based System to Predict Whether a Compound Is a Substrate of a Given Drug Transporter Using Its Chemical Structure.

Journal of pharmaceutical sciences
The aim of this study was to develop an in silico prediction system to assess which of 7 categories of drug transporters (organic anion transporting polypeptide [OATP] 1B1/1B3, multidrug resistance-associated protein [MRP] 2/3/4, organic anion transp...

New results on anti-synchronization of switched neural networks with time-varying delays and lag signals.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system a...

Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization.

Computational and mathematical methods in medicine
Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this st...

Adaptive contrast weighted learning for multi-stage multi-treatment decision-making.

Biometrics
Dynamic treatment regimes (DTRs) are sequential decision rules that focus simultaneously on treatment individualization and adaptation over time. To directly identify the optimal DTR in a multi-stage multi-treatment setting, we propose a dynamic stat...

An Artificial Intelligence System to Predict Quality of Service in Banking Organizations.

Computational intelligence and neuroscience
Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly c...

On the influence of spread constant in radial basis networks for electrical impedance tomography.

Physiological measurement
Electrical impedance tomography (EIT) is a non-invasive imaging technique. The main task of this work is to solve a non-linear inverse problem, for which several techniques have been suggested, but none of which gives a very high degree of accuracy. ...