๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Detector response unfolding using artificial neural networks

โœ Scribed by Senada Avdic; Sara A. Pozzi; Vladimir Protopopescu


Publisher
Elsevier Science
Year
2006
Tongue
English
Weight
719 KB
Volume
565
Category
Article
ISSN
0168-9002

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Sentence recognition using artificial ne
โœ Maciej Majewski; Jacek M. Zurada ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 275 KB

The paper describes an application of artificial neural networks (ANN) for natural language text reasoning. The task of knowledge discovery in text from a database, represented with a database file consisting of sentences with similar meanings but different lexico-grammatical patterns, was solved wi

Stormwater quantity and quality response
โœ Jianxun He; Caterina Valeo; Angus Chu; Norman F. Neumann ๐Ÿ“‚ Article ๐Ÿ“… 2010 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 188 KB

## Abstract This research investigates the potential impacts of climate change on stormwater quantity and quality generated by urban residential areas on an event basis in the rainy season. An urban residential stormwater drainage area in southeast Calgary, Alberta, Canada is the focus of future cl

Crystallization process optimization usi
โœ Prof. Dr. Ir. Alexandru Woinaroschy; Lect. Ir. Raluca Isopescu; Prof. Dr. Ir. La ๐Ÿ“‚ Article ๐Ÿ“… 1994 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 280 KB ๐Ÿ‘ 2 views

This paper presents a new procedure for optimization of continuous mixed suspensionmixed product removal (MSMPR) crystallizing systems. Owing to the difficulties of theoretical modelling, simulation of the MSMPR crystallization process is based on the use of artificial neural networks (ANN). The opt