- Category:
- AI-NN-PR
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- 1.52mb
- Update:
- 2013-04-17
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- mali
Description: Precipitation of short-term climate prediction is a very complex and important research topic. Intends to adopt in order to improve its ability to predict the the 1959-2011 monthly 74 atmospheric circulation feature series, monthly mean 500 hPa height field and monthly average sea surface temperature field, select the predictor extract the sample data using principal component analysis for the Synthesis factor. Artificial neural network using particle swarm optimization method, Xuancheng City in summer rainfall in short-term climate prediction model. 2007-2011 declared the city in summer precipitation forecast verification results show that the particle swarm optimization artificial neural network convergence speed, fewer iterations trial reported an average absolute error is 66.5 mm, the absolute value of the average relative error of 10.5 , high prediction accuracy, good application prospect.
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Application pso-bp PredictSummer Rainfall .pdf
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