DeepSun: Machine-Learning-as-a-Service for Solar Flare Prediction

TL;DR

DeepSun is a novel machine-learning-as-a-service platform that predicts solar flares using NASA's HMI data, offering remote API access and addressing a multi-class classification challenge in space weather forecasting.

Contribution

It introduces the first MLaaS tool for solar flare prediction, utilizing HMI data and multiple machine learning algorithms for multi-class classification.

Findings

Achieved multi-class solar flare prediction with high accuracy.

Provided a web-based API for remote access to prediction models.

Demonstrated the feasibility of MLaaS in space weather forecasting.

Abstract

Solar flare prediction plays an important role in understanding and forecasting space weather. The main goal of the Helioseismic and Magnetic Imager (HMI), one of the instruments on NASA's Solar Dynamics Observatory, is to study the origin of solar variability and characterize the Sun's magnetic activity. HMI provides continuous full-disk observations of the solar vector magnetic field with high cadence data that lead to reliable predictive capability; yet, solar flare prediction effort utilizing these data is still limited. In this paper, we present a machine-learning-as-a-service (MLaaS) framework, called DeepSun, for predicting solar flares on the Web based on HMI's data products. Specifically, we construct training data by utilizing the physical parameters provided by the Space-weather HMI Active Region Patches (SHARP) and categorize solar flares into four classes, namely B, C, M, X, according to the X-ray flare catalogs available at the National Centers for Environmental Information (NCEI). Thus, the solar flare prediction problem at hand is essentially a multi-class (i.e., four-class) classification problem. The DeepSun system employs several machine learning algorithms to tackle this multi-class prediction problem and provides an application programming interface (API) for remote programming users. To our knowledge, DeepSun is the first MLaaS tool capable of predicting solar flares through the Internet.