Fuzzy associative matrix

About: Fuzzy associative matrix is a research topic. Over the lifetime, 8027 publications have been published within this topic receiving 194790 citations.

Fuzzy Simple Additive Weighting Method by Preference Ratio

Abstract: Although simple additive weighting method (SAW) is the most popular approach for classical multiple attribute decision making (MADM), it is not practical any more if information is fuzzy. The existing methods of Fuzzy Simple Additive Weighting method (FSAW) apply defuzzification which distorts fuzzy numbers. Furthermore, most of the methods usually require lengthy and laborious manipulations. In this paper, we develop a new a fuzzy simple additive weighting method for multiple attribute decision making problems. To avoid defuzzification round off errors caused by multiplication or other arithmetic manipulations, fuzzy numbers are ranked prior to any fuzzy arithmetic in this method. The ranking is done by preference ratio concept which compares fuzzy numbers pairwise. Since this method eventually assigns crisp scores to alternatives, it is practical and more realistic. We also present three other algorithms for ranking or normalizing fuzzy numbers which are actually sub algorithms of the main method.

Dynamical Models of Stock Prices Based on Technical Trading Rules Part I: The Models

Abstract: In this paper, we use fuzzy systems theory to convert the technical trading rules commonly used by stock practitioners into excess demand functions which are then used to drive the price dynamics. The technical trading rules are recorded in natural languages where fuzzy words and vague expressions abound. In Part I of this paper, we will show the details of how to transform the technical trading heuristics into nonlinear dynamic equations. First, we define fuzzy sets to represent the fuzzy terms in the technical trading rules; second, we translate each technical trading heuristic into a group of fuzzy IF–THEN rules; third, we combine the fuzzy IF–THEN rules in a group into a fuzzy system; and finally, the linear combination of these fuzzy systems is used as the excess demand function in the price dynamic equation. We transform a wide variety of technical trading rules into fuzzy systems, including moving average rules, support and resistance rules, trend line rules, big buyer, big seller, and manipulator rules, band and stop rules, and volume and relative strength rules. Simulation results show that the price dynamics driven by these technical trading rules are complex and chaotic, and some common phenomena in real stock prices such as jumps, trending, and self-fulfilling appear naturally.

Orderings of fuzzy sets based on fuzzy orderings. Part I: the basic approach

Abstract: The aim of this paper is to present a general framework for comparing fuzzy sets with respect to a general class of fuzzy orderings. This approach includes known techniques based on generalizing the crisp linear ordering of real numbers by means of the extension principle, however, in its general form, it is applicable to any fuzzy subsets of any kind of universe for which a fuzzy ordering is known|no matter whether linear or partial.

Multilayered fuzzy behavior fusion for real-time reactive control of systems with multiple sensors

Abstract: Fuzzy linguistic rules provide an intuitive and powerful means for defining control behavior. Most applications that use fuzzy control feature a single layer of fuzzy inference, mapping a function from one or two inputs to equally few outputs. Highly complex systems, with large numbers of inputs, may also benefit from the use of qualitative linguistic rules if the control task is properly partitioned. This paper presents a modular fuzzy control architecture and inference engine that can be used to control complex systems. The control function is broken down into multiple local agents, each of which samples a subset of a large sensor input space. Additional fuzzy agents are employed to fuse the recommendations of the local agents. Real-time implementation without special hardware is possible by using singleton output values during fuzzy rule evaluation. A development tool is used to translate a fuzzy programming language offline for fast execution at run time. Using this system, a multilayered fuzzy behavior fusion based reactive control system has been implemented on an autonomous mobile robot, MARGE, with great success. MARGE won first place in Event III of the 1993 Robot Competition sponsored by the American Association for Artificial Intelligence.

Fuzzy relation equations and subsystems of fuzzy transition systems

Abstract: In this paper we study subsystems, reverse subsystems and double subsystems of a fuzzy transition system. We characterize them in terms of fuzzy relation inequalities and equations, as eigen fuzzy sets of the fuzzy quasi-order Q"@d and the fuzzy equivalence E"@d generated by fuzzy transition relations, and as linear combinations of aftersets and foresets of Q"@d and equivalence classes of E"@d. We also show that subsystems, reverse subsystems and double subsystems of a fuzzy transition system T form both closure and opening systems in the lattice of fuzzy subsets of A, where A is the set of states of T, and we provide efficient procedures for computing related closures and openings of an arbitrary fuzzy subset of A. These procedures boil down to computing the fuzzy quasi-order Q"@d or the fuzzy equivalence E"@d, which can be efficiently computed using the well-known algorithms for computing the transitive closure of a fuzzy relation.