AIMC Topic: Computer Simulation

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Novel plasticity rule can explain the development of sensorimotor intelligence.

Proceedings of the National Academy of Sciences of the United States of America
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, ...

Physical constraints, fundamental limits, and optimal locus of operating points for an inverted pendulum based actuated dynamic walker.

Bioinspiration & biomimetics
The inverted pendulum is a popular model for describing bipedal dynamic walking. The operating point of the walker can be specified by the combination of initial mid-stance velocity (v0) and step angle (φm) chosen for a given walk. In this paper, usi...

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm.

Computational intelligence and neuroscience
For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO...

How cockroaches exploit tactile boundaries to find new shelters.

Bioinspiration & biomimetics
Animals such as cockroaches depend on exploration of unknown environments, and their strategies may inspire robotic approaches. We have previously shown that cockroach behavior, with respect to shelters and the walls of an otherwise empty arena, can ...

Constructing general partial differential equations using polynomial and neural networks.

Neural networks : the official journal of the International Neural Network Society
Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transfo...

Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease.

Brain structure & function
Accurate diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, is very important for early treatment. Over the last decade, various machine learning methods have been proposed to predict disease status and clinica...

Building cell models and simulations from microscope images.

Methods (San Diego, Calif.)
The use of fluorescence microscopy has undergone a major revolution over the past twenty years, both with the development of dramatic new technologies and with the widespread adoption of image analysis and machine learning methods. Many open source s...

Spatially regularized machine learning for task and resting-state fMRI.

Journal of neuroscience methods
BACKGROUND: Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades.

Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

Computational intelligence and neuroscience
The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data o...