Machine learning & AI

AI models are powerful, but are they biologically plausible?

Artificial neural networks, ubiquitous machine-learning models that can be trained to complete many tasks, are so called because their architecture is inspired by the way biological neurons process information in the human ...

Computer Sciences

Researchers create digital humans that learn complex movements

Researchers at Meta's Artificial Intelligence Research Lab (Facebook) in the U.S. and at the University of Twente's Neuromechanical Modelling and Engineering Lab in the Netherlands (led by Prof.dr.ir Massimo Sartori), have ...

Computer Sciences

Trust the machine—it knows what it is doing

Machine learning, when used in climate science builds an actual understanding of the climate system, according to a study published in the journal Chaos by Manuel Santos Gutiérrez and Valerio Lucarini, University of Reading, ...

Engineering

Freeze! New model to protect ships from ice accretion

Researchers from Skoltech (Russia) and their colleagues from SINTEF (Norway) have developed a mathematical model of freezing water droplets moving in cold air. This model is a part of a joint RFBR-supported Russian-Norway ...

Energy & Green Tech

Blueprint may power up Saudi Arabia's wind energy future

A five-year study of wind energy potential in Saudi Arabia has culminated in a comprehensive blueprint for progressing the Kingdom's national wind energy strategy. Exhaustive high-resolution modeling was combined with a unique ...

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Simulation & Modeling for Acquisition, Requirements, and Trainin

Simulation is the imitation of some real thing, state of affairs, or process. The act of simulating something generally entails representing certain key characteristics or behaviours of a selected physical or abstract system.

Simulation is used in many contexts, including the modeling of natural systems or human systems in order to gain insight into their functioning. Other contexts include simulation of technology for performance optimization, safety engineering, testing, training and education. Simulation can be used to show the eventual real effects of alternative conditions and courses of action.

Key issues in simulation include acquisition of valid source information about the relevent selection of key characteristics and behaviours, the use of simplifying approximations and assumptions within the simulation, and fidelity and validity of the simulation outcomes.

This text uses material from Wikipedia, licensed under CC BY-SA