$EVWUDFW Recently, in the framework of Pattern Recognition, methods for combining several experts (Multi-Expert Systems, MES) in order to improve the recognition performance, have been widely investigated. A main problem of MES is that the combining rule should be able to take the right classification decision even when the experts disagree. Anyway, in critical cases, a reject decision is conve...

When combining classifiers in the Dempster-Shafer framework, Dempster’s rule is generally used. However, this rule assumes the classifiers to be independent. This paper investigates the use of other operators for combining non independent classifiers, including the cautious rule and, more generally, t-norm based rules with behavior ranging between Dempster’s rule and the cautious rule. Two stra...

The problem of combining beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's Rule has often been criticised, and many alternative rules for belief combination have been proposed in the literature. The consensus operator for combining beliefs has nice properties and produces more intuitive results than Dempster's r...

The paper discusses the problem of combining unreliable pieces of evidence in a (generalized) probabilistic setting. The popular Dempster's rule for combining evidence in Dempster-Shafer theory is criticized on two accounts. Firstly, Dempster's rule is claimed to be invalid, and secondly, the rule may fail to support intuitively acceptable conclusions. The reason for this is that the applicatio...

Multiple evidences based decision making is an important functionality for computers and robots. To combine multiple evidences, mathematical theory of evidence has been developed, and it involves the most vital part called Dempster’s rule of combination. The rule is used for combining multiple evidences. However, the combined result gives a counterintuitive conclusion when highly conflicting ev...

Association rule mining (ARM) is one of the most important tasks in data mining. In recent years, swarm intelligence algorithms have been effectively applied to ARM, and main challenge has achieve a balance between search efficiency quality mined rules. As novel algorithm, water wave optimization (WWO) algorithm widely used for combinatorial problems, with disadvantage that it tends fall into l...