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  • 1
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Journal of Agricultural Engineering Research 59 (1994), S. 19-31 
    ISSN: 0021-8634
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence review 12 (1998), S. 71-93 
    ISSN: 1573-7462
    Keywords: neuro-fuzzy modeling ; orthogonal least squares ; fuzzy rule reduction ; plant growth ; greenhouse climate
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract A hybrid neuro-fuzzy approach called the NUFZY system, which embeds fuzzy reasoning into a triple-layered network structure, has been developed to identify nonlinear systems. A set of membership functions at the input layer is partially linked with a layer of rules, using pre-set parameters. By means of a simplified centroid of gravity defuzzification method, the output becomes linear in the weights. Therefore, very fast estimation of the weight parameters can be achieved by using the orthogonal least squares (OLS) method, which also provides a method to efficiently remove the redundant fuzzy rules from the prototype rule base of the NUFZY system. In this paper, the NUFZY system is applied to identify lettuce growth and greenhouse temperature from real experimental data. Results show that the NUFZY model with the fast OLS training can perform quite well in predicting both lettuce growth and greenhouse temperature. In contrast to the mechanistic modeling procedures, the neuro-fuzzy approach offers an easier route and a fast way to build the nonlinear mapping of inputs and outputs. In addition, the resulting internal network structure of the NUFZY system is a self-explanatory representation of fuzzy rules. Under this frame, it is a perspective that one is able to incorporate the human knowledge in this approach, and, hopefully, to deduce any interpretable rules that describe the systems' behavior.
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 0178-515X
    Source: Springer Online Journal Archives 1860-2000
    Topics: Process Engineering, Biotechnology, Nutrition Technology
    Notes: Abstract Two methods for the calculation of optimal trajectories for the input variables of a fed-batch culture of hybridoma cells are compared. It pointed out that a gradient method based on Pontryagins' minimum principle based yields a significant better performance with respect to computational effort and the calculated minimum than a dynamic programming approach which has been presented in a previous paper [1] as the most suitable method.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    New York, NY [u.a.] : Wiley-Blackwell
    Biotechnology and Bioengineering 57 (1998), S. 155-163 
    ISSN: 0006-3592
    Keywords: endogenous respiration ; activated sludge ; multi-time scales ; identifiability ; observability ; model reduction ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: In this article, an autonomous four-compartment model that describes the endogenous respiration in an aerobic biodegradation process is proposed and analyzed theoretically. First, the multi-time scale of the system's behavior, to be taken into account in subsequent analyses, is emphasized. Then, an identifiability and observability study, given measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, is performed for use under practical circumstances, such as in state and parameter estimation. It appears that the process is observable, but not fully identifiable. Hence, for the identification of some of the model parameters, additional measurements or experiments, also indicated here, have to be performed. Furthermore, it is shown that, under quasi-steady state conditions which, in general, appear shortly after initialization of an endogenous respiration experiment, the model can be reduced significantly. Finally, results of parameter estimation from available data are presented and discussed. © 1998 John Wiley & Sons, Inc. Biotechnol Bioeng 57: 155-163, 1998.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
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