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《Journal of Anhui Agricultural Sciences》 2011-10
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Establishment and Application of Chlorella vulgari Growth Model Based on Optimizing BP Neural Network by Genetic Algorithm

QIN Peng et al(Guangzhou Microbial Institute,Guangzhou,Guangdong 510663)  
[Objective] The study aimed to discuss the establishment and application of Chlorella vulgari growth model on base of optimizing the BP neural network by genetic algorithm.[Method] The values of weight and threshold of BP neural network were optimized by using the genetic algorithm,and with this network model,the culturing time of C.vulgari and the residual glucose as the input and the thalli light density values(OD680) as the output,the growth state of C.vulgari in the 500 L multi-function biological reactor was modeled and the its application was discussed.[Result] BP neural network optimized by the genetic algorithm had the smaller error squares of generalization value than the one without optimization,so its predicted value was more close to the real value.T test showed that the established model was credible.The verification showed that the model had the good fitting degree and could well described the relationship of the biomass(OD680) of C.vulgari cultured in 500 L multi-function bioreactor with the residual glucose and culturing time.[Conclusion]The model established in the test could be used to the prediction of the test results,which had the guiding significance for controlling the culture of C.vulgari control.
【Fund】: 广州市科技支撑计划项目
【CateGory Index】: TP183
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