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Through the application of genetic algorithms (genetic algorithm, simplified as GA) and BP(Back Propation) neural network, I built a prediction model of roses diseases, in which I choose six indicators as the input of network, they are the minimum temperature, maximum temperature, average temperature, minimum humidity, maximum humidity, average humidity in the greenhouse, then I choose three diseases...
Based on the DE-BP (Back Propagation-Differential Evolution) neural network, the predicting model of concrete carbonization depth is presented. The precision of the model is checked using the monitoring data. The comparisons between the predicted results of the three models (BP model, GA-BP model and DE-BP model) and the monitoring data show that the precision of the present algorithm is higher with...
Back Propagation (BP) Neural Network has the ability of self-studying, self-adapting, fault tolerance and generalization. But there are some defaults in its basic application. Such as low convergence speed, local extremes and so on. So there are some limitations in practice. A quantitative forecast method based on the BP Neural Network improved by genetic algorithm (GA) is proposed in the paper. And...
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