Hochschulschrift | Online-Publikation
Reactions on surfaces with neural networks
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Sprache
-
Englisch
- Anmerkungen
-
Berlin, Techn. Univ., Diss., 2001
- Schlagwort
-
Palladium
Kristallfläche
Wasserstoff
Dissoziation
Oberflächenreaktion
Dissoziation
Ab-initio-Rechnung
Molekulardynamik
Neuronales Netz
- Urheber
- URN
-
urn:nbn:de:kobv:83-opus-1972
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:53 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Hochschulschrift
- Online-Publikation
Beteiligte
Ähnliche Objekte (12)
Artificial neural networks for the modelling and fault diagnosis of technical processes
Learning with recurrent neural networks
Stepwise evolutionary training strategies for hardware neural networks
An empirical investigation of neural networks, evolution strategies, and evolutionary trained neural networks and their application to some chemical engineering problems
Multilayer neural networks : learnability, network generation, and network simplification
Heterogeneous reactions of nitric acid and dinitrogen pentoxide on mineral dust surfaces : a Knudsen reactor study
Learning topography in neural networks : towards a better understanding of cortical topography
Bifurcations in discrete time neural networks : controlling complex network behaviour with inputs
Parameter identification for underdetermined systems arising in option pricing models and neural networks
Resource allocation in wireless networks : theory and algorithms
Financial risk management and portfolio optimization using artificial neural networks and extreme value theory
Strategy and governance of networks : cooperatives, franchising, and strategic alliances
Artificial neural networks for the modelling and fault diagnosis of technical processes
Learning with recurrent neural networks
Stepwise evolutionary training strategies for hardware neural networks
An empirical investigation of neural networks, evolution strategies, and evolutionary trained neural networks and their application to some chemical engineering problems
Multilayer neural networks : learnability, network generation, and network simplification
Heterogeneous reactions of nitric acid and dinitrogen pentoxide on mineral dust surfaces : a Knudsen reactor study
Learning topography in neural networks : towards a better understanding of cortical topography
Bifurcations in discrete time neural networks : controlling complex network behaviour with inputs
Parameter identification for underdetermined systems arising in option pricing models and neural networks
Resource allocation in wireless networks : theory and algorithms
Financial risk management and portfolio optimization using artificial neural networks and extreme value theory
Strategy and governance of networks : cooperatives, franchising, and strategic alliances
Artificial neural networks for the modelling and fault diagnosis of technical processes
Learning with recurrent neural networks
Stepwise evolutionary training strategies for hardware neural networks
An empirical investigation of neural networks, evolution strategies, and evolutionary trained neural networks and their application to some chemical engineering problems
Multilayer neural networks : learnability, network generation, and network simplification
Heterogeneous reactions of nitric acid and dinitrogen pentoxide on mineral dust surfaces : a Knudsen reactor study
Learning topography in neural networks : towards a better understanding of cortical topography
Bifurcations in discrete time neural networks : controlling complex network behaviour with inputs
Parameter identification for underdetermined systems arising in option pricing models and neural networks
Resource allocation in wireless networks : theory and algorithms
Financial risk management and portfolio optimization using artificial neural networks and extreme value theory