The Effect of a Dynamical Layer in Neural Network Prediction of Biomass in a Fermentation Process

Soufian, M; Soufian, Mustapha; Dempsey, M.J.

Abstract

In this paper, computational intelligence has been considered as a tool (software sensor) for state-estimation and prediction of biomass concentration in a simulated fermentation process. Two different paradigms of an artificial neural networks have been introduced as possible computational engines. Inclusion of process dynamics is inherent within the second paradigm, as a pre-processing layer. The constructed computational engines ‘infer’ the production of biomass from easily measured on-line variables. First and second-order non-linear optimisation methods are used to train the neural networks. It is shown that the use of the pre-processing layer which contains dynamical elements, produces better results and shows significant improvement in the convergence rate of the neural networks.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: The 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systems
• Start Date: Jun 1, 1998
• End Date: Jun 4, 1998
• Acceptance Date: Apr 3, 1998
• Online Publication Date: Jul 30, 2005
• Publication Date: Jun 1, 1998
• Deposit Date: May 5, 2017
• Publisher: Springer
• Series Title: Lecture Notes in Computer Science 1415
• Book Title: Proceedings of the 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systems
• Chapter Number: na
• ISBN: 3-540-64582-9
• Keywords: Biomass, fermentation, software sensor, neural networks,
• Public URL: http://researchrepository.napier.ac.uk/Output/840210