Please use this identifier to cite or link to this item: https://doi.org/10.1080/00986440701707685
Title: From database to operation design using a multiple model approach
Authors: Lakshminarayanan, S. 
Tun, K.
Takada, H.
Keywords: Genetic programming
Multiple models
Multivariate statistics
Nonparametric methods
Issue Date: Apr-2008
Source: Lakshminarayanan, S., Tun, K., Takada, H. (2008-04). From database to operation design using a multiple model approach. Chemical Engineering Communications 195 (4) : 462-477. ScholarBank@NUS Repository. https://doi.org/10.1080/00986440701707685
Abstract: We address the problem of estimating the input conditions (mixture compositions, operating temperature, pressure, etc.) that will result in manufacturing a product with the required properties using a data-based approach. A single-model type paradigm is shown to be unsuitable for all data sets or even for all output variables in a particular data set. A multiple-model type paradigm is therefore advocated. The input-output map is first obtained using one or more of the several modeling approaches. These models are then inverted to suggest operational strategies that will meet production goals. Several examples are presented to demonstrate the efficacy of the proposed methodology.
Source Title: Chemical Engineering Communications
URI: http://scholarbank.nus.edu.sg/handle/10635/63952
ISSN: 00986445
DOI: 10.1080/00986440701707685
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