Report
Using Random Hiveminds to Predict Solar Energetic Particles (SEPs)
| العنوان: | Using Random Hiveminds to Predict Solar Energetic Particles (SEPs) |
|---|---|
| المؤلفون: | Patrick M O’Keefe, Viacheslav Sadykov, Alexander Kosovichev, Irina N Kitiashvili, Vincent Oria, Gelu M Nita, Fraila Francis, Chun-Jie Chong, Paul Kosovich, Aatiya Ali, Russell D Marroquin |
| بيانات النشر: | United States: NASA Center for Aerospace Information (CASI), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Cybernetics, Artificial Intelligence and Robotics |
| الوصف: | The Problem: The use of conventional neural networks (CoNNs) to predict SEPs has become popular, but neural network models do not follow one-size-fits-all approaches and their chaotic natures can yield completely different results on identical data sets. Committees of neural networks identical in input features have been used to solve this problem by (Aminalragia et al., 2021), but they have the possibility of all agreeing together in lockstep and missing crucial information. The Solution: (O’Keefe et al., 2023) propose a solution consisting of neural network estimators in an ensemble, but with features randomly removed from them in a layout known as a random hivemind (RH). The decision weight, learning rate, and epoch count of each member in this ensemble are boosted in relation to how well its individual features perform in a chi-square test. |
| نوع الوثيقة: | Report |
| اللغة: | English |
| URL الوصول: | https://ntrs.nasa.gov/citations/20230006160 |
| ملاحظات: | 791926.02.09.02.03 80NSSC20K0302 80NSSC19K0068 NSF 1639683 NSF 1743321 NSF 1927578 NSF 1835958 NSF FDSS 1936361 |
| رقم الانضمام: | edsnas.20230006160 |
| قاعدة البيانات: | NASA Technical Reports |
| الوصف غير متاح. |