Development of New Models for Network Traffic Forecasting

Name: Development of New Models for Network Traffic Forecasting
Brand: LAP Lambert Academic Publishing
SKU: 9783330022492
Price: 45.57 EUR
Availability: InStock

Автор: Derman Akgöl, Mehmet Fatih Akay

Език:

Корици: С меки корици

Издател: LAP Lambert Academic Publishing

Наличност: Външен склад

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45.57 € 89.12 лв

The purpose of this work is to forecast the amount of network traffic in Transmission Control Protoc...

Информация за книгата

Автор

Derman Akgöl, Mehmet Fatih Akay

Език

Английски език

Корици

Книга - С меки корици

Издадена

2016

страници

112

EAN

9783330022492

Enbook ID

15764051

Издател

LAP Lambert Academic Publishing

Теглоt

185

Размери

150 x 220 x 8

Пълно описание

The purpose of this work is to forecast the amount of network traffic in Transmission Control Protocol/Internet Protocol (TCP/IP) -based networks by using different time lags and various machine learning methods including Support Vector Machines (SVM), Multilayer Perceptron (MLP), Radial Basis Function (RBF) Neural Network, M5P (a decision tree with linear regression functions at the nodes), Random Forest (RF), Random Tree (RT), and Reduced Error Prunning Error (REPTree), and statistical regression methods including Multiple Linear Regression (MLR) and Holt-Winters and compare the performance of statistical and machine learning methods. Two different Internet Service Providers' (ISPs) traffic data have been utilized to build traffic forecasting models. The first 66% of the data sets has been utilized as training sets and the rest has been used as test sets. The performance of the forecasting models for the data sets has been assessed using Mean Absulote Percentage Error (MAPE). The results show that SVM and M5P based models usually perform better than the ones obtained by the other methods.

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Development of New Models for Network Traffic Forecasting

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