Taking account of uncertain, imprecise and incomplete data in sustainability assessments in agriculture

Abstract

To manipulate incomplete, uncertain and hypothetic information about farms, the future evaluation software in the agriculture domain will have to make computations and combine fuzzy numerical values. The approach we propose relies on combination of incomplete, uncertain and hypothetic object values based on particular application of the Dempster-Shafer evidence theory. We then propose the integration of this approach in classic object oriented programming via the implementation of a C++ library. © 2014 Springer International Publishing.