Inaccurate feature extraction of risk data leads to low warning accuracy.Therefore,a multiple congestion risk warning method for emergency communication networks based on improved extreme learning machine is proposed.Collect and standardize data to preprocess risk data.With the support of improved extreme learning machine,calculate feature differences and feature vector weights to complete feature extraction of risk data.By weighting different data,construct a risk warning model,calculate the risk value of the communication network,classify the risk warning level,and achieve com-munication network risk warning.Through the above processes,the design of multiple congestion risk warning methods for emergency communication networks is completed.In the simulation experiment,compared with previous emergency commu-nication network multiple congestion risk warning methods,the designed multiple congestion risk warning method for emer-gency communication network based on improved extreme learning machine has a warning accuracy of 100％,and is more ac-curate in risks warning.
improved extreme learning machineemergency communication networksmultiple congestionrisk warning
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