Abstract:
This paper is about the estimation of tourism demand which is a foundation of all tourism-related business decisions ultimately rest. Here forecasting of tourism for goa for goa state. The state tourism is the key success for largely business. The tourism forecasting developmental methods are of two categories they are quantitative and the qualitative methods. The quantitative forecasting is of 3 sub categories they are non casual time series model, time series model and artificial intelligent techniques. A time series model explains a variable with regard to it's own past and a random disturbance term. for the forecasting of the tourism data mining algorithms like linear regression is used and the multiplicative linear regression is also used it is widely used in the modeling and statistics. Here we forecast for the next 12 months tourism by using the past data. Here the data is available in the two forms they are of foreign tourists visiting goa and the domestic tourists visiting goa every month. Because of the tourism forecasting it uses for not only government but also other sectors like hotels, tourism providers etc.
