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Computer Simulation

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Adaptive control and state error prediction of flexible manipulators using radial basis function neural network and dynamic surface control method.

PloS one
This paper introduces a novel control strategy for managing the uncertainties in flexible joint manipulators, incorporating a Radial Basis Function Neural Network (RBFNN) with Adaptive Dynamic Surface Control (ADSC). This strategy innovatively utiliz...

Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy.

Epilepsy research
INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing information in a simulated randomized clinical trial (RCT) for an anti-seizure medication, cenobamate, demon...

Purity control of simulated moving bed based on advanced fuzzy II controller.

PloS one
Simulated Moving Bed (SMB) is the optimal technology for chromatographic separation, but its process is complex and sensitive to numerous parameters that affect separation performance, making it difficult to control. In recent years, fuzzy controller...

Neural-network-based practical specified-time resilient formation maneuver control for second-order nonlinear multi-robot systems under FDI attacks.

Neural networks : the official journal of the International Neural Network Society
This paper presents a specified-time resilient formation maneuver control approach for second-order nonlinear multi-robot systems under false data injection (FDI) attacks, incorporating an offline neural network. Building on existing works in integra...

A strictly predefined-time convergent and anti-noise fractional-order zeroing neural network for solving time-variant quadratic programming in kinematic robot control.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a strictly predefined-time convergent and anti-noise fractional-order zeroing neural network (SPTC-AN-FOZNN) model, meticulously designed for addressing time-variant quadratic programming (TVQP) problems. This model marks the firs...

Event-driven figure-ground organisation model for the humanoid robot iCub.

Nature communications
Figure-ground organisation is a perceptual grouping mechanism for detecting objects and boundaries, essential for an agent interacting with the environment. Current figure-ground segmentation methods rely on classical computer vision or deep learning...

Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning.

SAR and QSAR in environmental research
Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating symptoms of dementia that downgrades to cholinergic neuronal loss in Alzheimer's disease. We developed a QSAR model to facilitate the identification of ...

Inertial primal-dual projection neurodynamic approaches for constrained convex optimization problems and application to sparse recovery.

Neural networks : the official journal of the International Neural Network Society
Second-order (inertial) neurodynamic approaches are excellent tools for solving convex optimization problems in an accelerated manner, while the majority of existing approaches to neurodynamic approaches focus on unconstrained and simple constrained ...

The reanalysis of a new strategy for groundwater level prediction using combined simulation of machine learning and Muskingum methods under ecological water replenishment.

Environmental research
Due to its multi-functionality, ecological water replenishment (EWR) has been an important measure for restoring aquifers. However, suitable prediction methods need to be selected for the unique fluctuation exhibited by groundwater level (GWL) in the...

Mediation CNN (Med-CNN) Model for High-Dimensional Mediation Data.

International journal of molecular sciences
Complex biological features such as the human microbiome and gene expressions play a crucial role in human health by mediating various biomedical processes that influence disease progression, such as immune responses and metabolic processes. Understa...