摘要

By "fusion" this work means integration of disparate types of data including (intervals of) real numbers as well as possibility/probability distributions defined over the totally-ordered lattice (R, <=) of real numbers. Such data may stem from different sources including (multiple/multimodal) electronic sensors and/or human judgement. The aforementioned types of data are presented here as different interpretations of a single data representation, namely Intervals' Number (IN). It is shown that the set F of INs is a partially-ordered lattice (F, <=) originating, hierarchically, from (R, <=). Two sound, parametric inclusion measure functions sigma:F-N x F-N -> [0,1] result in the Cartesian product lattice (F-N, <=) towards decision-making based on reasoning. In conclusion, the space (F-N, <=) emerges as a formal framework for the development of hybrid intelligent fusion systems/schemes. A fuzzy lattice reasoning (FLR) ensemble scheme, namely FLR pairwise ensemble, or FLRpe for short, is introduced here for sound decision-making based on descriptive knowledge (rules). Advantages include the sensible employment of a sparse rule base, employment of granular input data (to cope with imprecision/uncertainty/vagueness), and employment of all-order data statistics. The advantages as well as the performance of our proposed techniques are demonstrated, comparatively, by computer simulation experiments regarding an industrial dispensing application.

  • 出版日期2014-3