Artificial Intelligence for Space Applications

Girimonte, Daniela; Izzo, Dario

doi:10.1007/978-1-84628-943-9_12

Cited by 32 publications

(16 citation statements)

References 28 publications

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“…Additionally, large intelligent mechanical inventive systems necessitate development, which will implement obligatory changes upon arrival at extra-solar system target locales. Clearly AI will outperform humans and human intelligence [19,20].…”

Section: Life Cyclesmentioning

confidence: 99%

Astrovirology, Astrobiology, Artificial Intelligence: Extra-Solar System Investigations

Shapshak

2019

Global Virology III: Virology in the 21st Century

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This chapter attempts to encompass and tackle a large problem in Astrovirology and Astrobiology. There is a huge anthropomorphic prejudice that although life is unlikely, the just-right Goldilocks terrestrial conditions mean that the just-right balance of minerals and basic small molecules inevitably result in life as we know it throughout our solar system, galaxy, and the rest of the universe. Moreover, when such conditions on planets such as ours may not be quite right for the origin of life, it is popularly opined that asteroids and comets magically produce life or at the very least, the important, if not crucial components of terrestrial life so that life then blooms, when their fragments cruise the solar system, stars, and galaxies, and plummet onto appropriately bedecked planets and moons. It is no longer extraordinary to detect extraterrestrial solar systems. Moreover, since extra-solar system space exploration has commenced, this provides the problem of detecting life with enhanced achievability. Small organisms, which replicate outside of a living cell or host, would not be catalogued as viruses. How about viruses that cohabit with life? On the Earth, viruses are a major, if underestimated, condition of life-will that be the case elsewhere? Detection of extra-solar system viruses, if they exist, requires finding life, since viruses necessitate life to replicate. (It should be noted, though, that viruses could be detected through various types of portable ultra-microscopes, including Electron Microscopes (EM) (scanning and transmission) as well as Atomic Force Microscopes (AFM).) However, extra-solar system detection of life does not oblige that viruses exist ubiquitously. Viruses are important potential components of biospheres because of their multiple interactions and influence on evolution, although viruses are small and obligatory parasitic. In addition, nanotechnology-living or replicating nano-synthetic machine organisms might also be present out there, and require consideration as well. An imposing caveat is that, if found, could some extraterrestrial viruses and synthetic nanotechnological microorganisms infect humans? This chapter is dedicated to Ettore Majorana, who changed the view of the universe.

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Section: Life Cyclesmentioning

confidence: 99%

Astrovirology, Astrobiology, Artificial Intelligence: Extra-Solar System Investigations

Shapshak

2019

Global Virology III: Virology in the 21st Century

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“…The issues of AI management and control are important for developers and for civil society as well. Generally, intelligent control is an automatic control in which program algorithms are not predefined in advance, but formed by the control system itself, based on formalized descriptions of purposes, knowledge of possible actions, and information on current changes in the state of the environment [Girimonte & Izzo, 2007].…”

Section: What Is Artificial Intelligence?mentioning

confidence: 99%

Untitled

2019

ASL

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“…But to detect the failed sensor, other techniques were proposed by Gilmore (2002) and Napolitano et al (1995). Some works in the literature like Reis Junior et al 2017, Girimonte and Izzo (2007) and López-Martínez et al (2015) proposed the use of the ANN with thermal subsystems or others. Song and Zhang (2014) made a comparison between four algorithms for training the NN Quasi-Newton algorithm: the gradient descent algorithm with adaptive learning rate back-propagation algorithm, the gradient descent with momentum and adaptive learning rate back-propagation algorithm, and the Levenberg-Marquardt algorithm.…”

Section: Related Workmentioning

confidence: 99%

Simulation and Prediction for a Satellite Temperature Sensors Based on Artificial Neural Network

Abdelkhalek

Medhat

Ziedan

et al. 2019

J.Aerosp. Technol. Manag.

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Spacecrafts in space environment are exposed to several kinds of thermal sources such as radiation, albedo and emitted IR from the earth. The thermal control subsystem in spacecraft is used to keep all parts operating within allowable temperature ranges. A failure in one or many temperature sensors could lead to abnormal operation. Consequently, a prediction process must be performed to replace the missing data with estimated values to prevent abnormal behavior. The goal of the proposed model is to predict the failed or missing sensor readings based on artificial neural networks (ANN). It has been applied to EgyptSat-1 satellite. A backpropagation algorithm called Levenberg-Marquardt is used to train the neural networks (NN). The proposed model has been tested by one and two hidden layers. Practical metrics such as mean square error, mean absolute error and the maximum error are used to measure the performance of the proposed network. The results showed that the proposed model predicted the values of one failed sensor with adequate accuracy. It has been employed for predicting the values of two failed sensors with an acceptable mean square and mean absolute errors; whereas the maximum error for the two failed sensors exceeded the acceptable limits.

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Artificial Intelligence for Space Applications

Cited by 32 publications

References 28 publications

Astrovirology, Astrobiology, Artificial Intelligence: Extra-Solar System Investigations

Astrovirology, Astrobiology, Artificial Intelligence: Extra-Solar System Investigations

Untitled

Simulation and Prediction for a Satellite Temperature Sensors Based on Artificial Neural Network

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