Method for forecasting hybrid neural network and recognizing scenic spot meteorological elements

Abstract

The invention provides a method for forecasting a hybrid neural network and recognizing scenic spot meteorological elements. The method includes the steps of firstly, collecting and conducting normalization processing on data banks of meteorological stations; secondly, determining the number of RBF network hidden nodes established by the main meteorological elements of the meteorological stations through a subtractive clustering algorithm according to the data banks of the n meteorological stations; thirdly, obtaining RBF network model parameters of the m meteorological elements established by the n meteorological stations respectively through chaotic particle swarm optimization algorithm; fourthly, forecasting future meteorological element values of an assigned number of days of the n meteorological stations through optimum RBF network prediction models of the elements obtained by the n meteorological stations; fifthly, conducting autoregression adjustment on soft factor information of a certain scenic spot according to the n meteorological elements and forecasting the meteorological element values of the scenic spot; sixthly, establishing an ART2 network to recognize and record weather phenomena of the scenic spot. The method has the advantages that the hybrid neural network prediction models have good generalization performance, are high in accuracy for forecasting the weather in the scenic spot and have application value.

Description

Technical field [0001] The present invention involves a method of predicting and identifying the meteorological elements of mixed neural networks, which belongs to the field of atmospheric science and technology and computer application technology. Background technique [0002] The weather is the general term of the atmospheric state and its changes in a certain area.The weather system usually guides the atmospheric motion system with typical characteristics such as high -voltage, low -voltage and high -pressure ridge grooves of weather changes and distribution.The weather system is always in the process of constant occurrence, development and demise. Weather and weather changes in a region are the result of the comprehensive role of the atmosphere and the comprehensive role of the thermal process. [0003] The weather forecast is based on the principles of atmospheric science. The useTrends and climate disasters are scientifically predicted.The results of weather predictions pro...

AI Technical Summary

Problems solved by technology

However, because a certain local area is affected by the surrounding environmental conditions, such as the change of the population of a certain urban area, the influence of the vegetation coverage in the area, the influence of the spatial distance of the meteorological observation stations on the area, mountains, lakes and other factors in the area, Therefore, the data obtained by each meteorological observation station has a large change in the meteorological elements in a certain area, and these factors directly affect the meteorological element values ​​in this local area.

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