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- W2354923215 abstract "Evolutionary Neural Network (ENN) does not concern problems’internal mechanism,avoids the convergence to local brought by neural network model,but the ENN model is complicated because of too many parameters.This paper optimizes the Simple ENN (SENN) with individual encoding,fitness function,and develops self-adaptive crossing rate and mutation rate of the species,which are main factors that influence the performance of the ENN.Simulation of the concentration that SO2 contained in the air with its impact factors and the historical data shows that Optimized ENN (OENN) converges faster in the evolution process than the SENN,and performs better in the forecasting.The OENN model can be capable to supply valuable prediction data for environmental protection." @default.
- W2354923215 created "2016-06-24" @default.
- W2354923215 creator A5042306056 @default.
- W2354923215 date "2009-01-01" @default.
- W2354923215 modified "2023-09-22" @default.
- W2354923215 title "Research of forecasting of air quality based on optimization of Evolutionary Neural Network" @default.
- W2354923215 hasPublicationYear "2009" @default.
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