In this work we study overlap degrees expressed in terms of overlap functions. We present the basic properties that from our point of view must satisfy these overlap functions. We study a construction method, we analyze which t-norms are also overlap functions and we prove that if we apply particular aggregations to such functions we recover the overlap index between fuzzy sets as defined by Du...

this paper submitting the computation of optimize point of ordering in inventory control systems and particularly for continuous review of ordering system (r,q) by fuzzy logic method which similarly can be used for other ordering systems. since in the ordering models we cannot forecast the parameters like cost exactly, we have ambiguity. in this case using precise parameters may cause wrong dec...

In this work, by using norms (t-norms and t-conorms), Q-intuitionistic fuzzy subgroups of a group are defined investigated some their properties structured characteristics.

An n× n fuzzy matrix A is called regular if there is an n× n fuzzy matrix G such that AGA = A. We study the problem of characterizing those linear operators T on the fuzzy matrices such that T (X) is regular if and only if X is. Consequently, we obtain that T strongly preserves regularity of fuzzy matrices if and only if there are permutation matrices P and Q such that it has the form T (X) = P...

Due to the distributed nature of Denial-of-Service attacks, it is tremendously challenging to identify such malicious behavior using traditional intrusion detection systems in Wireless Sensor Networks (WSNs). In the current paper, a bio-inspired method is introduced, namely the cooperative-based fuzzy artificial immune system (Co-FAIS). It is a modular-based defense strategy derived from the da...

In this paper, we consider fuzzy inventory with backorder. First, we fuzzify the storing cost a, backorder cost b, cost of placing an order c, total demand r, order quantity q, and shortage quantity s as the triangular fuzzy numbers in the total cost. From these, we can obtain the fuzzy total cost. Using the signed distance method to defuzzify, we get the estimate of the total cost in the fuzzy...

Reinforcement Learning (RL) is a widely used learning paradigm for adaptive agents. Because exact RL can only be applied to very simple problems, approximate algorithms are usually necessary in practice. Many algorithms for approximate RL rely on basis-function representations of the value function (or of the Q-function). Designing a good set of basis functions without any prior knowledge of th...

In this paper we prove that a transitive fuzzy relation R on a set X can be extended to a total transitive fuzzy relation Q on X preserving the irreflexivity of R. This generalizes a classical theorem of Szpilrajn that asserts that any strict order on X can be extended to a total strict order on X . The extension theorem that we obtain will be used in the fuzzy analysis of a classical Richter t...