Industrial brewery modelling by using artificial network

被引:0
|
作者
Assidjo, E. [1 ]
Yao, B. [1 ]
Amane, D. [1 ]
Ado, G. [1 ]
Azzaro-Pantel, C. [2 ]
Davin, A. [1 ]
机构
[1] Laboratoire de Procédés Industriels de Synthèse et de l'Environnement, Département Génie Chimique et Agroalimentaire, Institut National Polytechnique Houphouët-Boigny, Yamoussoukro
[2] Laboratoire de Génie Chimique, Département Procédés et Systèmes Industriels, UMR CNRS 5503, Toulouse Cedex 1
关键词
Artificial neural network; Brewery; Fermentation; Modelling;
D O I
10.3923/jas.2006.1858.1862
中图分类号
学科分类号
摘要
Fermentation is a complex phenomenon well studied which still provides challenges to brewers. In this study, artificial neural network, precisely multi layer perceptron and recurrent one were utilised for modelling either static (yeast quantity to add to wort for fermentation) or dynamic (fermentation process) phenomena. In both cases, the simulated responses are very close to the observed ones with residual biases inferior to 4.5%. Thus, ANN models present good predictive ability confirming the suitability of ANN for industrial process modelling. © 2006 Asian Network for Scientific Information.
引用
收藏
页码:1858 / 1862
页数:4
相关论文
共 50 条
  • [31] Prediction of COD in industrial wastewater treatment plant using an artificial neural network
    Mesutoglu, Ozgul Cimen
    Gok, Oguzhan
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [32] Concentrate Grade Prediction in an Industrial Flotation Column Using Artificial Neural Network
    F. Nakhaeie
    A. Sam
    M. R. Mosavi
    Arabian Journal for Science and Engineering, 2013, 38 : 1011 - 1023
  • [33] Modelling of air temperature using remote sensing and artificial neural network in Turkey
    Sahin, Mehmet
    ADVANCES IN SPACE RESEARCH, 2012, 50 (07) : 973 - 985
  • [34] Modelling of nanostructured memristor device characteristics using Artificial Neural Network (ANN)
    Dongale, T. D.
    Patil, K. P.
    Vanjare, S. R.
    Chavan, A. R.
    Gaikwad, P. K.
    Kamat, R. K.
    JOURNAL OF COMPUTATIONAL SCIENCE, 2015, 11 : 82 - 90
  • [35] Modelling groundwater level fluctuations in urban areas using artificial neural network
    Malik, Ashish
    Bhagwat, Anjali
    GROUNDWATER FOR SUSTAINABLE DEVELOPMENT, 2021, 12
  • [36] Modelling and prediction of machining parameters in composite manufacturing using artificial neural network
    Ramanan, G.
    Samuel, G. Diju
    Sherin, S. Muthu
    Samuel, K.
    2ND INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING (ICAME 2018), 2018, 402
  • [37] Modelling of Turkey ' s net energy consumption using artificial neural network
    Sozen, Adnan
    Arcaklioglu, Erol
    Ozkaymak, Mehmet
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2005, 22 (2-3) : 130 - 136
  • [38] Modelling Energy Efficiency in Greenhouse Systems Using Artificial Neural Network (ANN)
    Yelmen, Bekir
    Cakir, M. Tank
    Sahin, H. Havva
    Kurt, Cengiz
    JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2021, 24 (01): : 151 - 160
  • [39] Modelling the behaviour of extended shear tab connection using artificial neural network
    Satarkar P.R.
    Londhe S.N.
    Dixit P.R.
    Suleiman M.F.
    Asian Journal of Civil Engineering, 2023, 24 (8) : 2767 - 2782
  • [40] Water quality modelling using artificial neural network and multivariate statistical techniques
    Isiyaka, Hamza Ahmad
    Mustapha, Adamu
    Juahir, Hafizan
    Phil-Eze, Philip
    MODELING EARTH SYSTEMS AND ENVIRONMENT, 2019, 5 (02) : 583 - 593