AIMC Topic: Nonlinear Dynamics

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A pruning feedforward small-world neural network based on Katz centrality for nonlinear system modeling.

Neural networks : the official journal of the International Neural Network Society Jul 16, 2020
Approaching to the biological neural network, small-world neural networks have been demonstrated to improve the generalization performance of artificial neural networks. However, the architecture of small-world neural networks is typically large and ...
Algorithms Neurons Nonlinear Dynamics Neural Networks, Computer
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Improving disaggregation models of malaria incidence by ensembling non-linear models of prevalence.

Spatial and spatio-temporal epidemiology Jul 4, 2020
Maps of disease burden are a core tool needed for the control and elimination of malaria. Reliable routine surveillance data of malaria incidence, typically aggregated to administrative units, is becoming more widely available. Disaggregation regress...
Nonlinear Dynamics Humans Incidence Prevalence Malaria Malaria, Falciparum
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Dynamical system based compact deep hybrid network for classification of Parkinson disease related EEG signals.

Neural networks : the official journal of the International Neural Network Society Jun 25, 2020
Electroencephalogram (EEG) signals accumulate the brain's spiking activities using standardized electrodes placed at the scalp. These cumulative brain signals are chaotic in nature and vary depending upon current physical and/or mental activities. Th...
Neural Networks, Computer Brain Parkinson Disease Humans Electroencephalography Nonlinear Dynamics
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Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

PloS one May 21, 2020
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of...
Models, Cardiovascular Male Boston Middle Aged Stroke Risk Assessment Cohort Studies Humans Hematocrit Electrocardiography Risk Factors Machine Learning Algorithms Nonlinear Dynamics Decision Trees Aged Prospective Studies Female
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Osteoporotic hip fracture prediction from risk factors available in administrative claims data - A machine learning approach.

PloS one May 19, 2020
OBJECTIVE: Hip fractures are among the most frequently occurring fragility fractures in older adults, associated with a loss of quality of life, high mortality, and high use of healthcare resources. The aim was to apply the superlearner method to pre...
Retrospective Studies Female Risk Factors Aged Aged, 80 and over Male Germany Humans Logistic Models Osteoporotic Fractures Machine Learning Nonlinear Dynamics Algorithms Hip Fractures
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Impulsive synchronization of coupled delayed neural networks with actuator saturation and its application to image encryption.

Neural networks : the official journal of the International Neural Network Society May 15, 2020
The actuator of any physical control systems is constrained by amplitude and energy, which causes the control systems to be inevitably affected by actuator saturation. In this paper, impulsive synchronization of coupled delayed neural networks with a...
Nonlinear Dynamics Pattern Recognition, Automated Humans Neural Networks, Computer Time Factors
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A Method to Extract Feature Variables Contributed in Nonlinear Machine Learning Prediction.

Methods of information in medicine May 7, 2020
BACKGROUND: Although advances in prediction accuracy have been made with new machine learning methods, such as support vector machines and deep neural networks, these methods make nonlinear machine learning models and thus lack the ability to explain...
Support Vector Machine Nonlinear Dynamics Machine Learning Algorithms Neural Networks, Computer
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Physics-informed neural networks for solving nonlinear diffusivity and Biot's equations.

PloS one May 6, 2020
This paper presents the potential of applying physics-informed neural networks for solving nonlinear multiphysics problems, which are essential to many fields such as biomedical engineering, earthquake prediction, and underground energy harvesting. S...
Algorithms Computer Simulation Nonlinear Dynamics Stochastic Processes Neural Networks, Computer
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Dynamic performances of a bird-like flapping wing robot under randomly uncertain disturbances.

PloS one May 5, 2020
The nonlinear dynamics of a bird-like flapping wing robot under randomly uncertain disturbances was studied in this study. The bird-like flapping wing robot was first simplified into a two-rod model with a spring connection. Then, the dynamic model o...
Biomimetics Nonlinear Dynamics Uncertainty Flight, Animal Wings, Animal Models, Theoretical Robotics Aircraft Animals Computer Simulation Birds Wind
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High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Biomedical physics & engineering express Apr 27, 2020
Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-...
Humans Reproducibility of Results Neoplasms Deep Learning Neural Networks, Computer Algorithms Computer Simulation Phantoms, Imaging Proton Therapy Protons Signal-To-Noise Ratio Image Processing, Computer-Assisted Radiotherapy Nonlinear Dynamics Scattering, Radiation
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