NEURAL NETWORKS - REDUCING ENERGY AND RAW-MATERIALS REQUIREMENTS

Authors
POPPE T OBRADOVIC D SCHLANG M
Citation
T. Poppe et al., NEURAL NETWORKS - REDUCING ENERGY AND RAW-MATERIALS REQUIREMENTS, Siemens Review, 1995, pp. 24-27
Citations number
NO
Categorie Soggetti
Engineering, Eletrical & Electronic
Journal title
Siemens Review → ACNP
ISSN journal
03022528
Year of publication
1995
Pages
24 - 27
Database
ISI
SICI code
0302-2528(1995):<24:NN-REA>2.0.ZU;2-4
Abstract
Unlike conventional control and regulation techniques, neural networks can modify their responses and dynamic characteristics through a lear ning process. In collaboration with the Industrial and Building System s Group, Siemens Corporate Research and Development Department has dev eloped specific applications that are saving resources and improving t he profitability of a number of industries.