This paper presents a new hybrid neuro-fuzzy model which is capable of learning structure and parameters by means of recursive binary space partitioning BSP. Introduction Neuro-fuzzy systems (NFSs) [1] combine the learning ability of artificial neural nets (ANNs) with the linguistic interpretation capacity of fuzzy inference systems (FISs) [2]. This work makes use of BSP (Binary Space Partition...

rating medicinal plants based on the total number of drug shows that the mint plant species, withgeneral name mentha, among the most consumption herbs that are used in various industries such aspharmaceutical, food, cosmetics and health. drying process, in order to maintain the quality andquantity of essential oil extraction have a great role in the processing medicinal plants. importantaspects...

Partitioning of quantified attributes is essential for mining association rules from quantified data and the Fuzzy approach solves the sharp boundary problem giving Fuzzy association rules having high interpretability and rich applicability. The paper presents automated partitioning of numerical data into Fuzzy sets based on k means clustering algorithm. This can be used as a pre-processing ste...

in this paper, we consider the production possibility set with n production units such that the following four principles that governs: inclusion observations, conceivability, immensity and convexity. our goal is to estimate the output of a same and new production unit with existing production possibility and amount of input is specified. so, initially we find the interval changes of each input...

Abstract. In this paper we explore the influence of the state-space partitioning into specific regions, when designing switched fuzzy controllers, to the stability performance of the system. For examination purposes we have designed switched fuzzy model and appropriate switched fuzzy controller for a hovercraft vehicle, as a typical nonholonomic system. The design is made for four different way...

Estimation of temporal fuzzy sets that model dynamic processes is discussed. It has been found that although poles of attraction can be estimated fairly well with different fuzzy partitioning algorithms, membership function estimates may fail in accurately describing dynamic changes within the observed signals. Two types of fuzzy partitioning algorithms are compared: fuzzy c-means (FCM) and fuz...

The poor scaling behavior of grid-partitioning fuzzy systems in case of increasing data dimensionality suggests using fuzzy systems with a scatter-partition of the input space. Jang has shown that zero-order Sugeno fuzzy systems are equivalent to radial basis function networks (RBFNs). Methods for nding scatter partitions for RBFNs are available, and it is possible to use them for creating scat...

Parsimony is very important in system modeling as it is closely related to model interpretability. In this paper, a scheme for constructing accurate and parsimonious fuzzy models by generating distinguishable fuzzy sets is proposed, in which the distinguishability of input space partitioning is measured by a so-called “local” entropy. By maximizing this entropy measure the optimal number of mer...