Interacting Multiple Model (IMM) algorithm is proved to be useful in tracking maneuvering targets. The tracking accuracy of the IMM can be further improved by modifying IMM to change its transition probabilities adaptively. A fuzzy logic controller (FLC) is designed to change the transition probabilities of IMM adaptively with innovation and rate of innovation as input parameters. The FLC selec...

We begin with a review of a well known class of networks, Classical Bayesian (CB) nets (also called causal probabilistic nets by some). Given a situation which includes randomness, CB nets are used to calculate the probabilities of various hypotheses about the situation, conditioned on the available evidence. We introduce a new class of networks, which we call Quantum Bayesian (QB) nets, that g...

Propagating possibilistic and probabilistic variables through a mapping yields a fuzzy random variable. We propose a method to attach probability intervals to events pertaining to the output variable. We show that this method is consistent with classical approaches to fuzzy random variables and that the obtained probability interval is the mean value of the fuzzy probability defined by viewing ...

In this work we suggest an approach to comparing fuzzy numbers motivated by a probabilistic view of the underlying uncertainty. An important aspect of the method suggested is its context dependency, the numbers being compared a€ect the process. We discuss the e€ect of decision attitude and show that this approach is particularly useful for aiding decision makers having a temperate decision atti...

Equipping hospital beds uses a great deal of a hospital''''s resources. Therefore, it is essential to consider the hospital beds'''' efficiency. To increase its efficiency, a fuzzy unrestricted model for managing hospital expenses is presented in this paper. The lack of beds in hospitals leads to patients’ admission loss and consecutively profit loss. On the other hand, increasing the bed count...

In this paper we analyze, mainly in a finitary setting, the consistency properties of fuzzy possibilities, interpreting them as instances of upper previsions and applying the basic notions of avoiding sure loss and coherence from the theory of imprecise probabilities. It ensues that fuzzy possibilities always avoid sure loss, but satisfy the stronger coherence condition only in a special case. ...

We applied genetic algorithms to fuzzy rule generation to compute expert system rules from data. We have attempted to improve on existing techniques for the automatic generation of fuzzy logic expert system rules with a method we call genetic data clustering (GDC). A genetic algorithm groups training data points by their degree of similarity, and fuzzy logic expert system rules are formed from ...

In this paper, some properties of Novel Weighted Averages that are related to the concepts of possibility theory are examined. It is shown that Novel Weighted Averages have certain interpretations in terms of addition of interactive interval or fuzzy constraints. To do this, alternative forms of Novel Weighted Averages are provided. In particular, an alternative form of Novel Weighted Averages ...

Methods are investigated in order to partition in k groups a set of n multivariate observation vectors located at neighboring geographic sites; applications include image segmentation, ecological or soil data cartography. In this perspective, the deterministic variant of the EM procedure described in Zhang (1992) for hidden Markov random fields is shown to be equivalent to the optimization of a...