
Novel Method of the Combination of Forecasts Based on Rough Sets
Author(s) -
Eslam Faik Ahmed,
Wang Jia Yang,
Maan Younis Abdullah
Publication year - 2009
Publication title -
journal of computer sciences/journal of computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.161
H-Index - 28
eISSN - 1552-6607
pISSN - 1549-3636
DOI - 10.3844/jcssp.2009.440.444
Subject(s) - computer science , rough set , data mining , artificial intelligence
Problem statement: A study in Analytic Hierarchy Process (AHP) had shown the problem of quantify the qualitative and the side Combined. Approach: So that problems were better resolved. The rough sets theory and AHP was introduced in the study, furthermore, these were united to create a completely new method of combination forecasts. Results: The results of numerical examples were shown to illustrate the interval AHP models reflecting the uncertainty of evaluations in nature. Conclusion: Therefore our method can be analyzed in order to make the best decision-making and makes combination forecast more objective. Further, the proposed procedure generates a set of easily understood rules that can be readily applied in knowledge-based