Knowledge based modular networks for process modelling and control

• Type: Article in International Scientific Journal
• Date: 2001

Authors

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

Journal

Title: Computers and Chemical Engineering

Vol. 25

Pages: 783-791

ISSN: 0098-1354

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 13 Citations

Scopus - 21 Citations

Scientific classification

FOS: Engineering and technology > Chemical engineering

CORDIS: Technological sciences > Engineering > Chemical engineering

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9