@inproceedings{914c7e8a81bc4c7ab8a0b8e2f7f9d5b7,
title = "Assessing Accessibility of Main-Belt Asteroids Using Support Vector Machines for Regression",
abstract = "The asteroid exploration is of immense scientific significance along with great economic benefits, and it makes the targets selection more significant because of the vast number of candidates. Accessibility is one of the most concerned issue when selecting targets. We construct an efficient assessment model to assess the accessibility of main-belt asteroids in multiple gravity assist trajectories. Optimization schemes with different parameters setting are compared and selected carefully to generate the training set of high-quality. Then, the assessment model based on Support Vector Regression is established. Finally, the accuracy of the assessment model is verified to be satisfactory. Discussions about accessibilities of targets for main-belt asteroids mission are also given based on large-scale results obtained from assessment model.",
keywords = "accessibility, gravity assist, machine learning, support vector machines for regression",
author = "Haohan Yang and Kuoxiang Zhang and Haibin Shang",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Chinese Automation Congress, CAC 2020 ; Conference date: 06-11-2020 Through 08-11-2020",
year = "2020",
month = nov,
day = "6",
doi = "10.1109/CAC51589.2020.9327355",
language = "English",
series = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6945--6950",
booktitle = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
address = "United States",
}