فهرست نشریات علمی دسترسی آزاد ایران

The need to perform a multiple-time series forecast arises many times in business and other circumstances. The Spherical Fuzzy Set (SFS) is the most popularly applied and competent method of solving uncertainty. SFS is an even newer utility compared to fuzzy sets and other type of fuzzy set. Previously there existed a gap in calculating the predicted data which is greater than 1. In order to tackle this form of deficiency we applied SFS in time series forecasting. This paper proposes a new technique (and of a higher order) based on spherical fuzzy sets technology that can allow forecasting of time series using an arbitrary dataset. Quantitative figures have shown that the RMSE is 54.9 percent lower (10.10 vs 22.41) and the AFE is 57.9 percent better (8.2 percent vs 19.5 ) than the benchmarks. This method has been applied and can increase the accuracy of prediction of the trends of HIV patients in Connecticut, and the complexity of data associations is included. The framework is rather effective in the modelling of error and imprecision providing forecasters with an adaptable model when making predictions. Taking the use of HIV patients in Connecticut as a case reference, the process indicates that it is more effective than the conventional methods. It has shown that the accuracy of forecasting significantly improved, which has the possible indicator in resources allocation and policy development in healthcare. The work will be of use to both the methods of prediction and healthcare administration, demonstrating the possible implications on the health of the population.