Fuzzy rough sets and multiple-premise gradual decision rules

We propose a new fuzzy rough set approach which, differently from most known fuzzy set extensions of rough set theory, does not use any fuzzy logical connectives (t-norm, t-conorm, fuzzy implication). As there is no rationale for a particular choice of these connectives, avoiding this choice permits to reduce the part of arbitrary in the fuzzy rough approximation. Another advantage of the new approach is that it is based on the ordinal properties of fuzzy membership degrees only. The concepts of fuzzy lower and upper approximations are thus proposed, creating a base for induction of fuzzy decision rules having syntax and semantics of gradual rules. The proposed approach to rule induction is also interesting from the viewpoint of philosophy supporting data mining and knowledge discovery, because it is concordant with the method of concomitant variations by John Stuart Mill. The decision rules are induced from lower and upper approximations defined for positive and negative relationships between credibility degrees of multiple premises, on one hand, and conclusion, on the other hand.     

Reduction about approximation spaces of covering generalized rough sets

The introduction of covering generalized rough sets has made a substantial contribution to the traditional theory of rough sets. The notion of attribute reduction can be regarded as one of the strongest and most significant results in rough sets. However, the efforts made on attribute reduction of covering generalized rough sets are far from sufficient. In this work, covering reduction is examined and discussed. We initially construct a new reduction theory by redefining the approximation spaces and the reducts of covering generalized rough sets. This theory is applicable to all types of covering generalized rough sets, and generalizes some existing reduction theories. Moreover, the currently insufficient reducts of covering generalized rough sets are improved by the new reduction. We then investigate in detail the procedures to get reducts of a covering. The reduction of a covering also provides a technique for data reduction in data mining.     

Axiomatic systems for rough sets and fuzzy rough sets

Rough set theory is an important tool for approximate reasoning about data. Axiomatic systems of rough sets are significant for using rough set theory in logical reasoning systems. In this paper, outer product method are used in rough set study for the first time. By this approach, we propose a unified lower approximation axiomatic system for Pawlak’s rough sets and fuzzy rough sets. As the dual of axiomatic systems for lower approximation, a unified upper approximation axiomatic characterization of rough sets and fuzzy rough sets without any restriction on the cardinality of universe is also given. These rough set axiomatic systems will help to understand the structural feature of various approximate operators.     

Chordal graphs and join spaces

A join space is an abstract model for partially ordered linear, spherical and projective geometries. A characterization for chordal graphs which are join spaces is given: a chordal graph is a join space if and only if it does not contain one of the two forbidden graphs as an induced subgraph.     

Data volume reduction in covering approximation spaces with respect to twenty-two types of covering based rough sets

In this paper, we investigate whether consistent mappings can be used as homomorphism mappings between a covering based approximation space and its image with respect to twenty-two pairs of covering upper and lower approximation operators. We also consider the problem of constructing such mappings and minimizing them. In addition, we investigate the problem of reducing the data volume using consistent mappings as well as the maximum amount of their compressibility. We also apply our algorithms against several datasets.     

The canonical join complex for biclosed sets

The canonical join complex of a semidistributive lattice is a simplicial complex whose faces are canonical join representations of elements of the semidistributive lattice. We give a combinatorial classification of the faces of the canonical join complex of the lattice of biclosed sets of segments supported by a tree, as introduced by the third author and McConville. We also use our classification to describe the elements of the shard intersection order of the lattice of biclosed sets. As a consequence, we prove that this shard intersection order is a lattice.     

Binary relations, interval structures and join spaces

We study correspondences between interval structures and hyperstructures.     

Triangular fuzzy decision-theoretic rough sets

Based on decision-theoretic rough sets (DTRS), we augment the existing model by introducing into the granular values. More specifically, we generalize a concept of the precise value of loss function to triangular fuzzy decision-theoretic rough sets (TFDTRS). Firstly, ranking the expected loss with triangular fuzzy number is analyzed. In light of Bayesian decision procedure, we calculate three thresholds and derive decision rules. The relationship between the values of the thresholds and the risk attitude index of decision maker presented in the ranking function is analyzed. With the aid of multiple attribute group decision making, we design an algorithm to determine the values of losses used in TFDTRS. It is achieved with the use of particle swarm optimization. Our study provides a solution in the aspect of determining the value of loss function of DTRS and extends its range of applications. Finally, an example is presented to elaborate on the performance of the TFDTRS model.     

Zero sets and interpolating sets in Fock spaces

An example is constructed to show that interpolating sets for Fock spaces are not necessarily zero sets.

     

Axiomatics for fuzzy rough sets

A fuzzy T-rough set consists of a set X and a T-similarity relation R on X, where T is a lower semi-continuous triangular norm. We generalize the Farinas-Prade definition for the upper approximation operator of a fuzzy T-rough set (X, R); given originally for the special case T = Min, to the case of arbitrary T. We propose a new definition for the lower approximation operator of (X,R). Our definition satisfies the two important identities and , as well as a number of other interesting properties. We provide axiomatics to fully characterize those upper and lower approximations.     

Topology vs generalized rough sets

This paper investigates the relationship between topology and generalized rough sets induced by binary relations. Some known results regarding the relation based rough sets are reviewed, and some new results are given. Particularly, the relationship between different topologies corresponding to the same rough set model is examined. These generalized rough sets are induced by inverse serial relations, reflexive relations and pre-order relations, respectively. We point that inverse serial relations are weakest relations which can induce topological spaces, and that different relation based generalized rough set models will induce different topological spaces. We proved that two known topologies corresponding to reflexive relation based rough set model given recently are different, and gave a condition under which the both are the same topology.     

A family of relative difference sets associated with Hjelmslev structures over finite projective spaces

In this note, we construct a new family of relative difference sets, with parameters n=q^d, m=q^d+...+q+1, k=q^d-1(q^d-1), ₁ =q^d-1(q^d-q^d-1-1) and ₂ =q^d-2(q-1)(q^d-1-1) where q is a prime power and d 2 an integer. The associated symmetric divisible designs admit natural epimorphisms onto the symmetric designs formed by points and hyperplanes in the corresponding projective spaces PG(d,q). As in the theory of Hjelmslev planes, points with the same image can be recognized from having the larger of the two possible joining numbers, and dually. More formally, these symmetric divisible designs are balanced c-H-structures (in the sense of Drake and Jungnickel [2]) with parameters c=q^d-2 (q-1)² and t=q^d-1 (q-1) over PG_d-1(d,q). These are the first examples of balanced non-uniform c-H-structures of type 2; they can be used in known constructions to obtain new balanced c-H-structures (for suitable c) of arbitrary type. In fact, all these results are special cases of a more general construction involving arbitrary difference sets.The author gratefully acknowledges the hospitality of the University of Waterloo and the financial support of NSERC under grant IS-0367.     

Lipschitz spaces and Suslin sets

Every bounded Suslin set in the plane is the set of eigenvalues of some bounded operator in a separable B-space.