A comprehensive evaluation method of wlan network load based on fahp-svm theory

Abstract

The present invention relates to a network load comprehensive evaluation method, in particular to a WLAN load comprehensive evaluation method based on an FAHP-SVM theory. The method comprises the following steps of 1 establishing a WLAN load comprehensive evaluation index system; 2 selecting a learning sample of a machine learning algorithmic; 3 adopting an analytic hierarchy process to determine the weights of the indexes in the WLAN load comprehensive evaluation index system; 4 utilizing a fuzzy comprehensive evaluation method to determine a network load evaluation value and a load evaluation grade of the sample data; 5 using the machine learning algorithmic to support the vector machine model training to obtain a network load automatic evaluation model; 6 using a WLAN load evaluation model to output a load value and a load grade corresponding to a network at this moment according to the inputted real-time WLAN performance data. The WLAN load comprehensive evaluation method based on the FAHP-SVM theory of the present invention utilizes the expert knowledge fully, also does not depend on the specific expert opinion, so that an evaluation result is objective. By using a machine learning classic algorithm SVM, the automatic evaluation of the WLAN performance is realized, and the labor cost is reduced substantially.

Description

technical field [0001] The invention relates to a method for comprehensive evaluation of network load, more specifically, a method for comprehensive evaluation of WLAN network load based on FAHP-SVM theory. Background technique [0002] In recent years, the number of smart terminals has increased, and the mobile Internet has gradually emerged, which has brought about continuous expansion of the scale of WLAN network construction. Compared with traditional wired networks, WLAN networks are more convenient to use, low in deployment costs, and flexible in use. Therefore, in many public scenarios, WLAN networks have begun to replace traditional networking methods. At present, large-scale WLAN networks have basically been established in major cities, but the management and optimization of WLAN networks are not very mature. WLAN optimization management faces problems such as complex network structure, many performance indicators, and massive data. [0003] At present, within eac...

AI Technical Summary

Problems solved by technology

This evaluation method not only reduces labor costs, but also realizes automatic evaluation, overcomes the disadvantages of strong subjectivity in judgment and high labor costs in the prior art, and achieves the purpose of evaluating WALN networks more comprehensively and objectively

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