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What is Dynamic Causal Rule

Handbook of Research on Fuzzy Information Processing in Databases
A dynamic causal rule consists of variables connected by arrows denoting the causal influences among the attributes. Two attributes A1 and A2 are linked by a causal arrow. Each causal link is assigned a polarity, and the link indicates the direction of the change. A dynamic causal rule is derived from a frequent dynamic attribute set.
Published in Chapter:
Applying Fuzzy Logic in Dynamic Causal Mining
Yi Wang (Cardiff University, UK)
Copyright: © 2008 |Pages: 21
DOI: 10.4018/978-1-59904-853-6.ch028
Abstract
This chapter applies fuzzy logic to a dynamic causal mining (DCM) algorithm and argues that DCM, a combination of association mining and system dynamics for discovering causality patterns, needs a potentially more substantive approach for the user to understand the nature of extracted rules and information in a variety of contexts. Furthermore, the author hopes that the use of fuzzy logic will not only assist the user to make better decisions, but also assist in a better understanding of future behaviour of the target system.
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