Hybrid software development (artificial neural network - Differential Evolution) applied to modelling and optimization of brewing process

• Grant number: 16/19004-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2016
• End date: November 30, 2017
• Field of knowledge: Engineering - Chemical Engineering
• Principal Investigator: José Celso Rocha
• Grantee: Maria Beatriz Takahashi
• Host Institution: Faculdade de Ciências e Letras (FCL-ASSIS). Universidade Estadual Paulista (UNESP). Campus de Assis. Assis , SP, Brazil

Abstract

The number of bioprocesses implemented in industrial scale has been increased dramatically since 20th century, which need methodologies that optimize their parameters, with the intention of make them economically viable and ensuring quality attributes of the product of interest. The quality of biotechnology products, as beer, can be modulated from changes in their ingredients proportions, as well as in operation parameters over the productive product. The combined experimental design (mixture and process variables) and the multiple optimization based on desirability function have demonstrated to be effective methodologies in the polynomial modelling and in the multiple optimization of this bioprocess, respectively. However, artificial intelligence techniques have been used as alternative of this modelling, optimizing a significant number of biological technologies, mainly the ones involved in biopharmaceuticals production. Therefore, the objective of this project is to implement a software combining Artificial Neural Network (ANN) and Differential Evolution to optimize the topology of an ANN to model the bioprocess involved in the Ale beer production and to use the optimized ANN in ingredients and operation parameters choice that ensure a beer with high acceptance rate on the market, by the Genetic Algorithm technique for multiple objective functions. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ROCHA, JOSE CELSO; PASSALIA, FELIPE JOSE; MATOS, FELIPE DELESTRO; TAKAHASHI, MARIA BEATRIZ; MASERATI, JR., MARC PETER; ALVES, MAYRA FERNANDA; DE ALMEIDA, TAMIE GUIBU; CARDOSO, BRUNA LOPES; BASSO, ANDREA CRISTINA; GOUVEIA NOGUEIRA, MARCELO FABIO. Automatized image processing of bovine blastocysts produced in vitro for quantitative variable determination. SCIENTIFIC DATA, v. 4, DEC 19 2017. (16/19004-4, 11/06179-7, 06/06491-2, 13/05083-1, 12/50533-2, 12/20110-2)