Semantic Scholar Open Access 2018 385 sitasi

Attractor reconstruction by machine learning.

Zhixin Lu B. Hunt E. Ott

Lihat Sumber DOI

Abstrak

A machine-learning approach called "reservoir computing" has been used successfully for short-term prediction and attractor reconstruction of chaotic dynamical systems from time series data. We present a theoretical framework that describes conditions under which reservoir computing can create an empirical model capable of skillful short-term forecasts and accurate long-term ergodic behavior. We illustrate this theory through numerical experiments. We also argue that the theory applies to certain other machine learning methods for time series prediction.

Topik & Kata Kunci

Medicine Mathematics Computer Science Physics

Penulis (3)

Zhixin Lu

B. Hunt

E. Ott

Format Sitasi

APA MLA BibTeX

Lu, Z., Hunt, B., Ott, E. (2018). Attractor reconstruction by machine learning.. https://doi.org/10.1063/1.5039508

Akses Cepat

Lihat di Sumber doi.org/10.1063/1.5039508

Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Total Sitasi: 385×
Sumber Database: Semantic Scholar
DOI: 10.1063/1.5039508
Akses: Open Access ✓