A team of researchers in the centre for robotics and neural systems at Plymouth University in England have developed an artificial intelligence neural network trained to classify the planets into five different categories based on their potential for habitability. This tool can be used in the future for interstellar space.
Researchers at the Plymouth University presented their work on their artificial neural network (Ann) at the European week of astronomy and space Sciences in Liverpool, England, 4 APR. As a neural network algorithm is built to learn as humans do, but are able to analyze much more data.
Christopher Bishop, Professor of computer science at the University of Edinburgh presented the team works on space of the Convention, stating that they are currently interested in using neural networks “in the priority study for a hypothetical interstellar spacecraft intelligent system scan exoplanets at a distance.”
To build their system, the researchers entered it served the spectral data of the five celestial bodies in our Solar system: Earth, predictions for early Earth, Mars, Venus and Titan, Saturn’s largest moon. Spectral data, data on the attributes of the atmospheric and orbital properties of the star body, and then was used to predict the habitability of planets and the moon. Ann then creates a “probability of life” measure based on these attributes.
Titan is considered the most habitable extraterrestrial body in our Solar system because it has liquid methane seas and rain.
While human cells are unable to form in Titan’s atmosphere, simulations have predicted the most stable molecule of Acrylonitrile (CH2CHCN) which can form cell membranes and was able to confirm its prevalence on Titan using spectral data.
Although the moon can support human life, or the greater part, if not all life on the planet Earth, that molecule can be a building block for another kind of life.
The Goddard center for Astrobiology Director: Michael Mumma said after the opening of the molecule abundance on Titan, “the ability to form stable Membrane for separating the internal environment from the outside is important because it provides the means contain chemicals long enough to allow them to interact.”
Meanwhile, the potential for spectral analysis is expected to improve dramatically in the coming years, with the James Webb space telescope (help) is the most complex space science telescope ever built and 100 times more powerful than the Hubble telescope, is expected to come on line in the next few years.
Unfortunately, the keyboard has been postponed until 2020, but if it comes out then, and not only their monitoring mission for familiarization with Anne, but it can also help to supply additional data to themselves, Ann and improvement of a neural network.
Sourse: sputniknews.com
