Analyses on the nature flow into Baiyangdian Lake based on the GA-grey wave forecasting model
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Abstract:
Seen from the long time-series of the nature flow into Baiyangdian Lake, it has a rule of the dry season and the wet season alternating. The grey wave forecasting model is applicable to research the rule’s evolutional trend. Using the genetic algorithm (GA) to optimize the first-order grey model（GM（1,1））’s iterative basic value α and background value coefficient β. Taking advantages of GA in efficient convergence and broad select range, basing on the GM(1,1) grey models established the GA-Grey wave forecasting model, thus use it study the trend of the nature flow into Baiyangdian Lake. The final analysis conclusion is that the GA-Grey wave forecasting model is obviously superior to the tradition grey wave forecasting model not only in matching information sequences but also in finding the changing characteristic of the information sequences, thus better forecast the changing of nature flow into Baiyangdian Lake. It shows the feasibility of GA-Grey wave forecasting model, providing the research of the variation of lake water resources quantity a new way.
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