A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is
African Journal of Business Management
In many studies, search engine data were efficient to analyze and forecast as an explanatory variable, including the tourism volumes predictions. However, the search data and the tourism volumes were always interfered by the noise. Without noise-processing, the predictive ability of search engine data might be weak, even invalid. As a method of noise-processing, Hilbert-Huang Transform (HHT) could deal with non-linear and non-stationary data. This study proposed a model with denoising anddoi:10.5897/ajbm2015.7945 fatcat:74sqjzhrevdqteecsprk5fxasm