Neural Network Algorithm for Particle Loading
An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given.
- Research Organization:
- Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC) (US)
- DOE Contract Number:
- AC02-76CH03073
- OSTI ID:
- 813621
- Report Number(s):
- PPPL-3808; TRN: US0303954
- Resource Relation:
- Other Information: PBD: 25 Apr 2003
- Country of Publication:
- United States
- Language:
- English
Similar Records
Removal of Congo Red from Aqueous Solution by Hydroxyapatite Nanoparticles Loaded on Zein as an Efficient and Green Adsorbent: Response Surface Methodology and Artificial Neural Network-Genetic Algorithm
Development of feed-forward neural network models for gas short-term load forecasting
Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.
Journal Article
·
Sat Sep 15 00:00:00 EDT 2018
· Journal of Polymers and the Environment
·
OSTI ID:813621
+3 more
Development of feed-forward neural network models for gas short-term load forecasting
Conference
·
Sat Dec 31 00:00:00 EST 1994
·
OSTI ID:813621
Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.
Program Document
·
Fri Jul 01 00:00:00 EDT 2016
· Buildings and Energy
·
OSTI ID:813621
+3 more