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Review on various models for time series forecasting

Authors :
Rajesh Wadhvani
Priyamvada
Source :
2017 International Conference on Inventive Computing and Informatics (ICICI).
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

The uncertainty in the time series data like wind speed, network traffic, stock price etc. makes the prediction of these data a very tedious task. In order to improve the performance of prediction, several models have been invented. In this paper, some of the models like autoregressive models and Holt-Winters have been discussed. Further, the various steps involved in obtaining the results and comparing the performance of above model have been examined.

Details

Database :
OpenAIRE
Journal :
2017 International Conference on Inventive Computing and Informatics (ICICI)
Accession number :
edsair.doi...........8cc4d0f4c3f89f854f78bcaf2ed26c66