Training an artificial neural network for recognizing electron collision patterns
- 1 January 2021
- journal article
- research article
- Published by Elsevier BV in Physics Letters A
Abstract
No abstract availableKeywords
Funding Information
- Ministry of Science and ICT (2019M1A2A2104119)
This publication has 30 references indexed in Scilit:
- Multi-Label ClassificationInternational Journal of Data Warehousing and Mining, 2007
- Solving the Boltzmann equation to obtain electron transport coefficients and rate coefficients for fluid modelsPlasma Sources Science and Technology, 2005
- Ensemble methods and data augmentation by noise addition applied to the analysis of spectroscopic dataAnalytica Chimica Acta, 2005
- Cross Sections for Electron Collisions with Water MoleculesJournal of Physical and Chemical Reference Data, 2005
- Electron-impact dissociation of oxygenThe Journal of Chemical Physics, 1993
- The feasibility of using neural networks to obtain cross sections from electron swarm dataIEEE Transactions on Plasma Science, 1991
- A comparative study of ordinary cross-validation, v-fold cross-validation and the repeated learning-testing methodsBiometrika, 1989
- The Momentum Transfer Cross Section for Electrons in Argon in the Energy Range 0 - 4 eVAustralian Journal of Physics, 1977
- Electron impact induced electronic excitation and molecular dissociationInternational Journal for Radiation Physics and Chemistry, 1976
- Absolute Total Electron Scattering Cross Sections inandfor Low Electron EnergiesPhysical Review B, 1966