{"title":"Network Traffic Prediction Based on Neural Network","authors":"G. Feng","doi":"10.1109/ICITBS.2015.136","DOIUrl":null,"url":null,"abstract":"Predicting and modeling network traffic is always an important subject in network capability studying. The aim of this article is to explore a new network model in order to describe and predict the network character accurately. Firstly wavelet neural network is investigated and its disadvantages are analyzed. In order to overcome disadvantages of wavelet neural network, genetic algorithm is used to optimize weight and threshold of neural network. At last, the proposed algorithm is used in network traffic prediction and the results show the proposed scheme has good performance.","PeriodicalId":51314,"journal":{"name":"Big Data","volume":"57 12","pages":"527-530"},"PeriodicalIF":2.6000,"publicationDate":"2015-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/ICITBS.2015.136","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 19
Abstract
Predicting and modeling network traffic is always an important subject in network capability studying. The aim of this article is to explore a new network model in order to describe and predict the network character accurately. Firstly wavelet neural network is investigated and its disadvantages are analyzed. In order to overcome disadvantages of wavelet neural network, genetic algorithm is used to optimize weight and threshold of neural network. At last, the proposed algorithm is used in network traffic prediction and the results show the proposed scheme has good performance.
Big DataCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
9.10
自引率
2.20%
发文量
60
期刊介绍：
Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.
Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.
Big Data coverage includes:
Big data industry standards,
New technologies being developed specifically for big data,
Data acquisition, cleaning, distribution, and best practices,
Data protection, privacy, and policy,
Business interests from research to product,
The changing role of business intelligence,
Visualization and design principles of big data infrastructures,
Physical interfaces and robotics,
Social networking advantages for Facebook, Twitter, Amazon, Google, etc,
Opportunities around big data and how companies can harness it to their advantage.
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