New antimicrobial quinolones - 1. Mathematical and neural modeling of diethyl ethoxymethylene malonate synthesis

Oniscu, C; Dumitrascu, A; Curteanu, S; Pintilie, L; Cernatescu, C; Mocanu, A

HERO ID

4936241

Reference Type

Journal Article

Year

2007

HERO ID 4936241
In Press No
Year 2007
Title New antimicrobial quinolones - 1. Mathematical and neural modeling of diethyl ethoxymethylene malonate synthesis
Authors Oniscu, C; Dumitrascu, A; Curteanu, S; Pintilie, L; Cernatescu, C; Mocanu, A
Journal Romanian Biotechnology Letters
Volume 12
Issue 1
Page Numbers 3089-3101
Abstract The most difficult and costly step in the industrial manufacturing of antimicrobial quinolones is the synthesis of ethoxymethylene malonate (EMME), which is influenced by three main parameters: ethyl orthoformate/diethyl malonate molar ratio, acetic anhydride/diethyl l malonate molar ratio and time. In order to establish the optimum reaction conditions a planned factorial experiment of second-degree order was accomplished, in which the real values of the parameters and their limits Of variation were chosen arbitrarily. Feedforward neural networks with a single hidden layer were used in direct and inverse modeling of the process, to predict the yield of the reaction for different reaction conditions or the reaction conditions for a pre-established yield. Both mathematical modeling and the neural modeling of EMME obtaining process enabled to settle the optimum values of the parameters for a maximum yield in EMME.
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Keyword antimicrobial quinolones; diethyl ethoxymethylene malonate; mathematical modeling; regression equation; neural networks modeling