AIMC Topic: Neural Networks, Computer

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Fusing Swarm Intelligence and Self-Assembly for Optimizing Echo State Networks.

Computational intelligence and neuroscience
Optimizing a neural network's topology is a difficult problem for at least two reasons: the topology space is discrete, and the quality of any given topology must be assessed by assigning many different sets of weights to its connections. These two c...

Prediction of Peptide and Protein Propensity for Amyloid Formation.

PloS one
Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo str...

An Effective and Novel Neural Network Ensemble for Shift Pattern Detection in Control Charts.

Computational intelligence and neuroscience
Pattern recognition in control charts is critical to make a balance between discovering faults as early as possible and reducing the number of false alarms. This work is devoted to designing a multistage neural network ensemble that achieves this bal...

Predictive Modeling in Race Walking.

Computational intelligence and neuroscience
This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers' training events and they are used to predict the result...

Fuzzy wavelet plus a quantum neural network as a design base for power system stability enhancement.

Neural networks : the official journal of the International Neural Network Society
In this study, we introduce an indirect adaptive fuzzy wavelet neural controller (IAFWNC) as a power system stabilizer to damp inter-area modes of oscillations in a multi-machine power system. Quantum computing is an efficient method for improving th...

Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

Ergonomics
UNLABELLED: Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling...

Stability and synchronization of memristor-based fractional-order delayed neural networks.

Neural networks : the official journal of the International Neural Network Society
Global asymptotic stability and synchronization of a class of fractional-order memristor-based delayed neural networks are investigated. For such problems in integer-order systems, Lyapunov-Krasovskii functional is usually constructed, whereas simila...

Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

Neural networks : the official journal of the International Neural Network Society
Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of...

Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network.

Computational intelligence and neuroscience
An artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term x(t + 6). The performance predi...

Towards dropout training for convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demons...