Improving Accuracy in Importance Sampling: An Integrated Approach with Fuzzy-Strata Sampling

Several statistical approaches have been developed to analyze the sampling of huge data and information. There are three significant factors for comparison of the strength of these methods that are argued in this paper; the proposed method is a compatible approach to various types of sampling methods and applied to improve the sampling efficiency and decrease uncertainties to reach accuracy in results. In argued methods, each element just belongs to one category and/ or strata, but in our approach, each element includes all groups with one exception that membership values are different. The case study results show that the proposed Fuzzy Strata Sampling (FSS) method better measures uncertainty and accuracy rate than the other existing sampling methods.