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International Journal of Nonlinear Analysis and Applications، جلد ۱۲، شماره Special Issue، صفحات ۹۵۹-۹۷۰
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عنوان انگلیسی The implementation of sax and random projection for motif discovery on the orbital elements and the resonance argument of asteroid
چکیده انگلیسی مقاله Motif discovery has emerged as one of the most useful techniques in processing time-series data. One of the implementations of motif discovery is in case study 1:1 mean motion resonance (MMR) in the astronomy field. This study aims to build a computational model and its implementation to process time-series data and predict 1:1 MMR from asteroid orbital elements in time-series form. This model proposes Symbolic Aggregate approximation (SAX) and Random Projection (RP) algorithms implemented in the Python programming language. Some experiments involving ten asteroids’ orbital elements data have been carried out to validate the program. From the results obtained, we conclude that our computational model can predict the location of the motif and with which planet the motif is found for 1:1 resonance to occur.
کلیدواژه‌های انگلیسی مقاله Motif discovery, Astrophysics, Random projection, time series
نویسندگان مقاله Lala Septem Riza |
Department of Computer Science Education, Faculty of Mathematics and Natural Science Education, Universitas Pendidikan Indonesia, Bandung, Indonesia.

Muhammad Naufal Fazanadi |
Department of Computer Science Education, Faculty of Mathematics and Natural Science Education, Universitas Pendidikan Indonesia, Bandung, Indonesia.

Judhistira Aria Utama |
Department of Physics Education, Faculty of Mathematics and Natural Science Education, Universitas Pendidikan Indonesia, Bandung, Indonesia.

Taufiq Hidayat |
Astronomy Research Division, Faculty of Mathematics and Natural Science, Institut Teknologi Bandung, Bandung, Indonesia.

Khyrina Airin Fariza Abu Samah |
Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Melaka Kampus Jasin, Melaka, Malaysia.

نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_5543_7c7f9ec52fa68c9087e64cad3b3eeb38.pdf
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