Recently, a theoretical fuzzy IR system, based on gradual inclusion measures, has been proposed [1]. In this model, derived from the division of fuzzy relations, the gradual inclusion of a query in a document is modeled by a fuzzy implication. In previous papers, we have shown that, under some assumptions, this model can be seen as a Vector Space Model. This paper also studies other interpretat...

In this paper, we propose a reinforcement learning method called a fuzzy Q-learning where an agent determines its action based on the inference result by a fuzzy rule-based system. We apply the proposed method to a soccer agent that intercepts a passed ball by another agent. In the proposed method, the state space is represented by internal information the learning agent maintains such as the r...

Hierarchical structures and uncertainty measures are two main aspects in granular computing, approximate reasoning and cognitive process. Typical hesitant fuzzy sets, as a prime extension of fuzzy sets, are more flexible to reflect the hesitance and ambiguity in knowledge representation and decision making. In this paper, we mainly investigate the hierarchical structures and uncertainty measure...

A sum of real numbers equals the mutual entropy of a fuzzy set and its complement set. A " fuzzy " or multivalued set is a point in a unit hypercube. Fuzzy mutual (Kullback) entropy arises from the logarithm of a unique measure of fuzziness. The proof uses the logistic map, a diffeomorphism that maps extended real space onto the fuzzy cube embedded in it. The logistic map equates the sum of a v...

in this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming (abbreviated to fflp) problems. also, we employ linear programming (lp) with equality constraints to find a nonegative fuzzy number vector x which satisfies ax =b, where a is a fuzzy number matrix. then we investigate the existence of a positive solution of fully fuzzy linear system (ffls).

In this work, we propose an approach for computing the compromised solution of an LR fuzzy linear system by using of a ranking function when the coefficient matrix is a crisp mn matrix. To do this, we use expected interval to find an LR fuzzy vector, X , such that the vector (AX ) has the least distance from (b) in 1 norm and the 1 cut of X satisfies the crisp linear system AX = b ...

This paper presents a novel approach to estimate the pose position of the degraded face images using fuzzy vector representation. We focus on the development of fuzzy-manifold as an interpolation line between all the available learning data and the fuzzy distance calculation as the classifier. Crisp-based vector of the face image is firstly transformed into fuzzy-based vector, to deal with the ...

we introduce and  study  fuzzy (co-)inner product and fuzzy(co-)norm of hyperspaces. in this regard by considering  the notionof hyperspaces, as a generalization of vector spaces, first we willintroduce the notion of fuzzy (co-)inner product in hyperspaces and will apply it to formulate the notions offuzzy (co-)norm and fuzzy (co-)orthogonality  in hyperspaces. inparticular, we will prove that ...

we show that the category of convergence approach spaces is a simultaneously reective and coreective subcategory of the category of latticevalued limit spaces. further we study the preservation of diagonal conditions, which characterize approach spaces. it is shown that the category of preapproach spaces is a simultaneously reective and coreective subcategory of the category of lattice-valued p...

We present a neuro-fuzzy system for character recognition from printed documents using a fuzzy Hough transform technique. For each character pattern, fuzzy Hough transform extracts information from the standard Hough transform accumulator cells into a number of fuzzy sets. These basic fuzzy sets are combined by t-norms to synthesize additional fuzzy sets whose heights form an n-dimensional feat...