Fuzzy Rules have been shown to be very useful in modeling relationships between variables that have a high degree of uncertainty or ambiguity. A major question in regards to learning fuzzy rule bases is how to handle interactions between rules of overlapping coverage. Structures, such as Yager’s HPS (Hierarchical Prioritized Structure), have been proposed to answer this question. In this paper,...

A hierarchical fuzzy sliding-mode control is proposed to achieve asymptotic stability and favorable decoupling performance. In this approach, the nonlinear system is decoupled into several subsystems and the state response of each subsystem can be designed to be governed by a corresponding sliding surface. Then the whole system is controlled by a hierarchical sliding-mode controller. The propos...

bilevel linear programming  is a decision making problem with a two-level decentralized organization. the textquotedblleft leadertextquotedblright~ is in the upper level and the textquotedblleft followertextquotedblright, in the lower. making a decision at one level affects that at the other one. in this paper, bilevel linear programming  with inexact parameters has been studied and a method is...

This paper describes a new class of neuro-fuzzy models, called Reinforcement Learning Hierarchical NeuroFuzzy Systems (RL-HNF). These models employ the BSP (Binary Space Partitioning) and Politree partitioning of the input space [Chrysanthou,1992] and have been developed in order to bypass traditional drawbacks of neuro-fuzzy systems: the reduced number of allowed inputs and the poor capacity t...

The hierarchical TOPSIS model used in this article is able to grasp the ambiguity exists in the utilized information and the fuzziness appears in the human judgments and preferences. The use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits: (1) being a systematic model and straight forward one for working on; and (2) capable of capturing human's appraisal of ambiguity wh...

Regarding to the diversified needs of domestic and global customers and various products of domestic and global competitors, importance of agility in supply chain management becomes more important. Suppliers have to provide materials and essential resources of manufacturers in a short time without any lead time.In this research, we identified many criteria for agility in sanitation supply chain...

This paper presents a new hierarchical tree approach to clustering fuzzy data, namely extensional tree (ET) clustering algorithm. It defines a dendrogram over fuzzy data and using a new distance between fuzzy numbers based on -cuts. The present work is based on hierarchical clustering algorithm unlike existing methods which improve FCM to support fuzzy data. The Proposed ET clustering algorithm...

most organizations need to information systems to survive and thrive. therefore, they should seriously protect their information assets. creating structured and justifiable exchanges between cost, security and mission control systems security risks is essential. this is important in the planning and development of such systems. initial appropriate decisions can reduce costs and increase ease of...

In this thesis, an intelligent fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates is developed. The proposed system uses a Hierarchical Fuzzy Logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases. A fuzzy logic system is developed to model and predict three month quarterly interest rate flu...