Prediction method of network resource and environment coupling relationship

Abstract

The invention discloses a prediction method for a network resource and environment coupling relation. The method comprises the following steps: carrying out the preprocessing of an original incompleteparameter set through a missing value processing method and a service expansion method based on multi-dimensional fuzzy mapping, and obtaining a preliminary parameter set; performing feature construction on the preliminarily obtained parameter set through a feature construction method based on multi-dimensional environmental parameters to obtain data with stronger representation capability; S3, fusing forward sequence search, backward sequence search and a simulated annealing algorithm to perform dimension reduction on the features of the data obtained in the step S2, thereby reducing the variable space of each dimension and the complexity of multi-dimensional representation model training; a model training method based on a decision tree is adopted to carry out training learning prediction on data, and accurate description of network resources under complex environment constraints is realized. According to the method, the missing value can be quickly and accurately complemented, andthe purpose of improving the model efficiency can be achieved while the prediction precision is improved.

Description

technical field [0001] The present invention relates to the technical field of network communication, and more specifically, to a method for predicting the coupling relationship between network resources and the environment. Background technique [0002] In the actual network communication process, due to problems such as equipment failures and environmental mutations, environment sensing devices collect incomplete or inaccurate data, which in turn leads to abnormal representation results of network resource status. Whether the characterization of network resource status is accurate will have a great impact on the utilization of network resources. [0003] If the incomplete or inaccurate data collected by the environment sensing device is not filled, the data will be entered into the analysis model with a value of 0 by default. Whether it is in the training or testing phase, the input of 0 value will greatly affect the model's ability to Normal data response, resulting in i...

AI Technical Summary

Problems solved by technology

[0010] In order to solve the current actual network communication process, due to problems such as equipment failure and environmental mutation, the environmental sensing equipment collects incomplete or inaccurate data, while the existing technology faces the situation of missing data, and directly deletes the missing data. The value method, or the missing value is filled with the previous row of data or the mean value. This conventional fitting method solves the problem of low accuracy of the prediction results of multidimensional nonlinear functions. A prediction method for the coupling relationship between network resources and the environment is proposed. It can quickly and accurately complete missing values ​​and improve prediction accuracy

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