|Communications on Applied Electronics|
|Foundation of Computer Science (FCS), NY, USA|
|Volume 7 - Number 2|
|Year of Publication: 2017|
|Authors: Ashwini N., Rajshekar Patil M.|
Ashwini N., Rajshekar Patil M. . A Study on Forecaster Model using Time Series Data. Communications on Applied Electronics. 7, 2 ( May 2017), 34-39. DOI=10.5120/cae2017652604
Many physical and artificial phenomena can be described by time series. The prediction of any such phenomenon could be complex and interesting. The ability to forecast the future is mainly based on only past data, which leads to strategic advantages and will be key to success in organizations. Time series forecasting allows the modeling of complex systems as black-boxes, being a focus of attention in several research arenas. There are several methods for time series data which mainly depends whether the data is linear or nonlinear. In this paper a survey on the forecasting method based on the different types of the data presented. This survey will mainly concentrate based on neural network, evolutionary computation etc. in solution development of forecasting models and rules, continued with hybrid forecaster mainly.