Minimal Polynomial Logic (MPL) is a generalisation of classical propositional logic which allows truth values in the continuous interval 0; 1] and in which propositions are represented by multi-variate polynomials. In previous work 7] we have introduced some properties of MPL and shown that it has two possible semantics: a) it can be considered as a logic for expressing, handling and computing ...

Fuzzy c-means clustering and its derivatives are very successful on many clustering problems. However, fuzzy c-means clustering and similar algorithms have problems with high dimensional data sets and a large number of prototypes. In particular, we discuss hard c-means, noise clustering, fuzzy c-means with a polynomial fuzzifier function and its noise variant. A special test data set that is op...

From a set of a partially ordered tasks, one goal of the project scheduling problem is to compute earliest starting dates, latest starting dates and floats of the different tasks, and to identify critical tasks. When durations of tasks are not precisely known, the problem is much trickier. Recently we provided polynomial algorithms to compute upper bound of activity floats in the interval-value...

Minimal Polynomial Logic (MPL) is a generalisation of classical propositional logic which allows truth values in the continuous interval 0; 1] and in which propositions are represented by multi-variate polynomials. In previous work 7] we have introduced some properties of MPL and shown that it has two possible semantics: a) it can be considered as a logic for expressing, handling and computing ...

AbstructTraditionally, prototype-based fuzzy clustering algorithms such as the Fuzzy C Means (FCM) algorithm have been used to find “compact” or “filled” clusters. Recently, there have been attempts to generalize such algorithms to the case of hollow or “shell-like” clusters, i.e., clusters that lie in subspaces of feature space. The shell clustering approach provides a powerful means to solve ...

Since its introduction, answer set programming has been generalized in many directions, to cater to the needs of real-world applications. As one of the most general “classical” approaches, answer sets of arbitrary propositional theories can be defined as models in the equilibrium logic of Pearce. Fuzzy answer set programming, on the other hand, extends answer set programming with the capability...

In this paper, different semi-active control strategies for non-linear quarter car model equipped with controllable magneto-rheological (MR) shock absorbers and fuzzy logic controller are compared. Polynomial model is selected to characterize the experimental results of MR shock absorber. A combination of Forward Fuzzy Logic Controller (FFLC) and Inverse Fuzzy Logic Controller (IFLC) is designe...

During the last two decades, Group for intelligent systems at Mathematical faculty in Belgrade has developed several theorem provers for different kind of formal systems. Lately, we have turned our attention to fuzzy logic and development of the corresponding theorem prover. The first step is to find the suitable axiomatization, i.e., the formalization of fuzzy logic that is sound, complete and...

This investigation presents a novel method of image processing using the polynomial bidirectional hetero-associative network (PBHAN). This network can be used for industrial application of optical character recognition. According to the results of detailed simulations, the PBHAN has a higher capacity for pattern pair storage than do the conventional bidirectional associative memories and fuzzy ...