Hybrid neural modeling of bioprocesses using functional link networks

被引：15
|
作者：
Harada, LHP [1 ]
Da Costa, AC [1 ]
Maciel, R [1 ]
机构：
[1] Univ Estadual Campinas, FEQ, DPQ, BR-13081970 Campinas, SP, Brazil
来源：
APPLIED BIOCHEMISTRY AND BIOTECHNOLOGY | 2002年 / 98卷 / 1-9期
关键词：
extractive alcoholic fermentation; functional link networks; hybrid model; bioprocess; modeling;
D O I：
10.1385/ABAB:98-100:1-9:1009
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
The objective of this work was to develop a model for an extractive ethanol fermentation in a simple and rapid way. This model must be sufficiently reliable to be used for posterior optimization and control studies. A hybrid neural model was developed, combining mass and energy balances with neural networks, which describe the process kinetics. To determine the best model, two structures of neural networks were compared: the functional link networks and the feedforward neural networks. The two structures are shown to describe well the process kinetics, and the advantages of using the functional link networks are discussed.
引用
收藏
页码：1009 / 1023
页数：15
相关论文
共 50 条
  • [1] Hybrid neural modeling of bioprocesses using functional link networks
    Layse H. P. Harada
    Aline C. da Costa
    Rubens Maciel Filho
    Applied Biochemistry and Biotechnology, 2002, 98-100 : 1009 - 1023
  • [2] Classification of Web Logs Using Hybrid Functional Link Artificial Neural Networks
    Behera, Ajit Kumar
    Dash, Ch. Sanjeev Kumar
    Dehuri, Satchidananda
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON FRONTIERS OF INTELLIGENT COMPUTING: THEORY AND APPLICATIONS (FICTA) 2014, VOL 1, 2015, 327 : 255 - 263
  • [3] Modeling of an intelligent pressure sensor using functional link artificial neural networks
    Patra, JC
    van den Bos, A
    ISA TRANSACTIONS, 2000, 39 (01) : 15 - 27
  • [4] Study on sensor modeling using Chebyshev functional link artificial neural networks
    Jun, L
    Yu, D
    ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 2017 - 2020
  • [5] Modeling and identification of flexible link using neural networks
    Rao, SR
    Bandyopadhyay, B
    Seth, B
    PROCEEDINGS OF IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY 2000, VOLS 1 AND 2, 2000, : 237 - 242
  • [6] Nonlinear Functional Modeling Using Neural Networks
    Rao, Aniruddha Rajendra
    Reimherr, Matthew
    JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2023, 32 (04) : 1248 - 1257
  • [7] Hybrid metabolic flux analysis/artificial neural network modeling of bioprocesses
    Teixeira, A
    Alves, C
    Alves, PM
    Carrondo, MJT
    Oliveira, R
    HIS 2005: 5th International Conference on Hybrid Intelligent Systems, Proceedings, 2005, : 411 - 416
  • [8] Control of bioprocesses by neural networks
    Ritzka, A
    Ulber, R
    Hitzmann, B
    Scheper, T
    CHEMIE INGENIEUR TECHNIK, 2002, 74 (1-2) : 149 - 152
  • [9] Hybrid metabolic flux analysis/artificial neural network modeling of bioprocesses
    Teixeira, A. (ana.teixeira@dq.fct.unl.pt), Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior; Operador Nacional do Sistema Eletrico - ONS (IEEE Computer Society):
  • [10] Extraction of Hard Exudates using Functional Link Artificial Neural Networks
    Bhaskar, K. Udaya
    Kumar, E. Pranay
    2015 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC), 2015, : 420 - 424
12345