Multidimensional Fuzzy Reasoning Method Based on Weight of Fuzzy Neural Network
Wenyu Liu · 2008
Interpolative reasoning is type of important reasoning approaches under sparse rules. Interpolative reasoning in one dimension has been researched widely, but the research in multi-dimension is lacking and a few existing approaches have some faults. These methods not only cannot guarantee the convexity of result, but also cannot consider the relation between many variables, weight of influenced conclusion. It leads to more error of inferential result. Interpolative reasoning in multi-dimension is an important research aspect of interpolative reasoning, in order to get better conclusion under multidimensional sparse rules condition, we propose a fuzzy multidimensional reasoning method based on weight of fuzzy neural network, which moreover can keep the convexity of the reasoning consequence.