Knowledge based modular networks for process modelling and control

• Tipo: Artigo em Revista Científica Internacional
• Data: 2001

Autores

Peres, J. (Autor) FEUP; R. Oliveira (Autor) FEUP; S. Feyo de Azevedo (Autor) FEUP

Revista

Título: Computers and Chemical Engineering

Vol. 25

Páginas: 783-791

ISSN: 0098-1354

Editora: Elsevier

Indexação

ISI Web of Knowledge - 13 Citações

Scopus - 21 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia química

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia química

Outras Informações

ID Authenticus: P-000-VM0

DOI: 10.1016/s0098-1354(01)00665-2

Abstract (EN): This payer addresses methods of knowledge engineering for chemical and biochemical process modelling and control. The concept of knowledge Based Modular (KBM) Networks is presented. KBM networks represent a method of expressing and combining different types of knowledge usually available for modelling chemical and biochemical processes: mechanistic, heuristic and knowledge hidden in process data records, The Expectation Maximisation (EM) algorithm is employed to optimally combine the modules within the KBM network. The concepts are illustrated with an application to a baker's yeast production process. The results show that it is possible to obtain more accurate process description when all available sources of knowledge are incorporated in the process model.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 9