1,818 research outputs found
A Fuzzy Petri Nets Model for Computing With Words
Motivated by Zadeh's paradigm of computing with words rather than numbers,
several formal models of computing with words have recently been proposed.
These models are based on automata and thus are not well-suited for concurrent
computing. In this paper, we incorporate the well-known model of concurrent
computing, Petri nets, together with fuzzy set theory and thereby establish a
concurrency model of computing with words--fuzzy Petri nets for computing with
words (FPNCWs). The new feature of such fuzzy Petri nets is that the labels of
transitions are some special words modeled by fuzzy sets. By employing the
methodology of fuzzy reasoning, we give a faithful extension of an FPNCW which
makes it possible for computing with more words. The language expressiveness of
the two formal models of computing with words, fuzzy automata for computing
with words and FPNCWs, is compared as well. A few small examples are provided
to illustrate the theoretical development.Comment: double columns 14 pages, 8 figure
State-Based Control of Fuzzy Discrete Event Systems
To effectively represent possibility arising from states and dynamics of a
system, fuzzy discrete event systems as a generalization of conventional
discrete event systems have been introduced recently. Supervisory control
theory based on event feedback has been well established for such systems.
Noting that the system state description, from the viewpoint of specification,
seems more convenient, we investigate the state-based control of fuzzy discrete
event systems in this paper. We first present an approach to finding all fuzzy
states that are reachable by controlling the system. After introducing the
notion of controllability for fuzzy states, we then provide a necessary and
sufficient condition for a set of fuzzy states to be controllable. We also find
that event-based control and state-based control are not equivalent and further
discuss the relationship between them. Finally, we examine the possibility of
driving a fuzzy discrete event system under control from a given initial state
to a prescribed set of fuzzy states and then keeping it there indefinitely.Comment: 14 double column pages; 4 figures; to be published in the IEEE
Transactions on Systems, Man, and Cybernetics--Part B: Cybernetic
Optimized Hierarchical Power Oscillations Control for Distributed Generation Under Unbalanced Conditions
Control structures have critical influences on converter-interfaced
distributed generations (DG) under unbalanced conditions. Most of previous
works focus on suppressing active power oscillations and ripples of DC bus
voltage. In this paper, the relationship between amplitudes of the active power
oscillations and the reactive power oscillations are firstly deduced and the
hierarchical control of DG is proposed to reduce power oscillations. The
hierarchical control consists of primary and secondary levels. Current
references are generated in primary control level and the active power
oscillations can be suppressed by a dual current controller. Secondary control
reduces the active power and reactive power oscillations simultaneously by
optimal model aiming for minimum amplitudes of oscillations. Simulation results
show that the proposed secondary control with less injecting negative-sequence
current than traditional control methods can effectively limit both active
power and reactive power oscillations.Comment: Accepted by Applied Energ
Discovering Fuzzy Functional Dependencies as Semantic Knowledge in Large Databases
Fuzzy functional dependency (FFD) is a kind of semantic knowledge and can be discovered from a large volume of business data. Sectional FFD and Attribute FFD are discussed so as to reflect semantics of the business world and express useful information that is natural for people to comprehend. The experimental results on an insurance data set show that the proposed method can extract knowledge efficiently and effectively
Temporal Association Rule Mining in China’s Closed-end Fund Data
Financial market plays an important role in economy. Although funds developed only a few years in China, it has been a focal point in research and practice. The conventional methods analyzing fund data are fundamental analysis and technical analysis. Data mining can extract implicit, previously unknown and potentially useful knowledge from data. This paper presents the new technique to analyze China’s closed-end fund data and temporal association rules (TAR) are discovered which reflect the relationship among open price, close price, trading volume and grail index. Experimental results show some interesting outcomes
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