AIMC Topic: Computer Simulation

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Using Neural Network Force Fields to Ascertain the Quality of Simulations of Liquid Water.

The journal of physical chemistry. B
Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the level, inc...

Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control.

Neural networks : the official journal of the International Neural Network Society
Our brain can be recognized as a network of largely hierarchically organized neural circuits that operate to control specific functions, but when acting in parallel, enable the performance of complex and simultaneous behaviors. Indeed, many of our da...

Automatic Parking System Based on Improved Neural Network Algorithm and Intelligent Image Analysis.

Computational intelligence and neuroscience
This research designs an intelligent parking system including service application layer, perception layer, data analysis layer, and management layer. The network system adopts opm15 system, and the parking space recognition adopts improved convolutio...

ESIDE: A computationally intelligent method to identify earthworm species (E. fetida) from digital images: Application in taxonomy.

PloS one
Earthworms (Crassiclitellata) being ecosystem engineers significantly affect the physical, chemical, and biological properties of the soil by recycling organic material, increasing nutrient availability, and improving soil structure. The efficiency o...

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.

PloS one
BACKGROUND: Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.

Artificial neural network-based output power prediction of grid-connected semitransparent photovoltaic system.

Environmental science and pollution research international
The solar photovoltaic system is an emerging renewable energy resource. The performance of the solar photovoltaic system is predicted based on the historical experimental dataset. In this work, the real-time prediction models are developed for the ou...

Using synthetic data generation to train a cardiac motion tag tracking neural network.

Medical image analysis
A CNN based method for cardiac MRI tag tracking was developed and validated. A synthetic data simulator was created to generate large amounts of training data using natural images, a Bloch equation simulation, a broad range of tissue properties, and ...

Neural-Network Based Modeling of I/O Buffer Predriver under Power/Ground Supply Voltage Variations.

Sensors (Basel, Switzerland)
This paper presents a neural-network based nonlinear behavioral modelling of I/O buffer that accounts for timing distortion introduced by nonlinear switching behavior of the predriver electrical circuit under power and ground supply voltage (PGSV) va...

Machine learning - Predicting Ames mutagenicity of small molecules.

Journal of molecular graphics & modelling
In modern drug discovery, detection of a compound's potential mutagenicity is crucial. However, the traditional method of mutagenicity detection using the Ames test is costly and time consuming as the compounds need to be synthesised and then tested ...

Energy Management Expert Assistant, a New Concept.

Sensors (Basel, Switzerland)
In recent years, interest in home energy management systems (HEMS) has grown significantly, as well as the development of Voice Assistants that substantially increase home comfort. This paper presents a novel merging of HEMS with the Assistant paradi...