This paper illustrates a subjective safety-cost based design-decision support framework using fuzzy logic and evidential reasoning approaches. The framework is divided into three parts. The first one is for safety analysis and synthesis including fuzzy rule-based safety estimation using the fuzzy rule-based evidential reasoning (FRB-ER) approach, as well as the safety synthesis using the eviden...

Aiming to solving the problem that the evidence information based on Dezert-Smarandache (DSm) model can not be fused effectively in Conditional Evidential Network based on Smets/DS model (ENC), a reasoning method in Conditional Evidential Network based on DSm model is proposed. First, the conditional reasoning formular in Conditional Evidential Network based on DSm model is proved and the reaso...

The main purpose of this article is to introduce the evidential reasoning approach, a research methodology, for decision making under uncertainty. Bayesian framework and Dempster-Shafer theory of belief functions are used to model uncertainties in the decision problem. We first introduce the basics of the DS theory and then discuss the evidential reasoning approach and related concepts. Next, w...

The complexity of the domains in which expert systems are expected to operate requires that they be capable of "reasoning* 1 about their actions It has been argued that expert systems must reason from evidential information i.e., uncertain, incomplete, and occasionally inaccurate information [LOW82a|. As a consequence, a model for reasoning about control must deal with several problems being ab...

In this paper we describe a novel method for evidential reasoning [1]. It involves mod­ elling the process of evidential reasoning in three steps, namely, evidence structure con­ struction, evidence accumulation, and deci­ sion making. The proposed method, called 'RfS, is novel in that evidence strength is associated with an evidential support relationship (an argu­ ment) between a pair of stat...

This paper describes a framework for combining and assessing subjective evidence from different sources. The approach is based on the DempsterShafer belief theory, but instead of using Dempster’s rule we introduce a new rule called the consensus operator that is based on statistical inference. We show how this framework can be applied to subjective evidential reasoning.