Assessment and Monitoring Quality of Communications Network Based on Feature Selection and Probabilistic Neural Network

Cui Feng Du; Qiang Xu; Ji Hua Li

doi:10.4028/www.scientific.net/AMR.846-847.836

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Assessment and Monitoring Quality of...

Assessment and Monitoring Quality of Communications Network Based on Feature Selection and Probabilistic Neural Network

Abstract:

Using feature selection and neural networks to experiment the data, then we bring a warning model of user complaints. It is the core that using the known information of network index sample to analyze and discriminate. First, the training samples need to be extract, because there are too many features in training data will have an adverse impact on machine learning classification algorithm. Using extraction method to explore the feature subset with feature, feature subset is a set of feature vectors, then the feature vectors are input into the probability neural network prediction, find out the best features quantum set. This model can be achieved using the MATLAB software, and it is operational, and it can be extended to the network quality assessment and monitoring practice.

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

836-839

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.836

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Online since:

November 2013

Authors:

Cui Feng Du*, Qiang Xu, Ji Hua Li

Keywords:

Early Warning, Feature Selection, Network Monitoring, Network Quality Evaluation, Probabilistic Neural Network

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* - Corresponding Author

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