• Journal of Microbiology and Biotechnology
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• v.22 no.7
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• pp.939-946
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• 2012

Antibiotic production with Streptomyces sindenensis MTCC 8122 was optimized under submerged fermentation conditions by artificial neural network (ANN) coupled with genetic algorithm (GA) and Nelder-Mead downhill simplex (NMDS). Feed forward back-propagation ANN was trained to establish the mathematical relationship among the medium components and length of incubation period for achieving maximum antibiotic yield. The optimization strategy involved growing the culture with varying concentrations of various medium components for different incubation periods. Under non-optimized condition, antibiotic production was found to be $95{\mu}g/ml$, which nearly doubled ($176{\mu}g/ml$) with the ANN-GA optimization. ANN-NMDS optimization was found to be more efficacious, and maximum antibiotic production ($197{\mu}g/ml$) was obtained by cultivating the cells with (g/l) fructose 2.7602, $MgSO_4$ 1.2369, $(NH_4)_2PO_4$ 0.2742, DL-threonine 3.069%, and soyabean meal 1.952%, for 9.8531 days of incubation, which was roughly 12% higher than the yield obtained by ANN coupled with GA under the same conditions.

• Journal of Biomedical Engineering Research
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• v.29 no.3
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• pp.231-238
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• 2008

Nelder-Mead downhill simplex method (DSM), a kind of deterministic optimization algorithms, has been used extensively for magnetoencephalography(MEG) dipolar source localization problems because it dose not require any functional differentiation. Like many other deterministic algorithms, however, it is very sensitive to the choice of initial positions and it can be easily trapped in local optima when being applied to complex inverse problems with multiple simultaneous sources. In this paper, some modifications have been made to make up for DSM's limitations and improve the accuracy of DSM. First of all, initial point determination method for DSM using magnetic fields on the sensor surface was proposed. Secondly, Univariant-DSM combined DSM with univariant method was proposed. To verify the performance of the proposed method, it was applied to simulated MEG data and practical MEG measurements.