A survey on forecasting of time series data

Time series analysis and forecasting future values has been a major research focus since years ago. Time series analysis and forecasting in time series data finds it significance in many applications such as business, stock market and exchange, weather, electricity demand, cost and usage of products such as fuels, electricity, etc. and in any kind of place that has specific seasonal or trendy changes with time. The forecasting of time series data provides the organization with useful information that is necessary for making important decisions. In this paper, a detailed survey of the various techniques applied for forecasting different types of time series dataset is provided. This survey covers the overall forecasting models, the algorithms used within the model and other optimization techniques used for better performance and accuracy. The various performance evaluation parameters used for evaluating the forecasting models are also discussed in this paper. This study gives the reader an idea about the various researches that take place within forecasting using the time series data.