In this article, the author generalizes Dempster’s rule, Yager’s rule, and Dubois-Prade’s rule for belief functions combination in order to be applicable to hyper-power sets according to the Dezert-Smarandache (DSm) Theory. A comparison of the rules with the DSm rule of combination is further presented.

In this study, we introduce and study a concept of distributed fuzzymodeling. Fuzzy modeling encountered so far is predominantly of a centralizednature by being focused on the use of a single data set. In contrast to this style ofmodeling, the proposed paradigm of distributed and collaborative modeling isconcerned with distributed models which are constructed in a highly collaborativefashion. I...

The two dominant schemes for rule-learning, C4.5 and RIPPER, both operate in two stages. First they induce an initial rule set and then they refine it using a rather complex optimization stage that discards (C4.5) or adjusts (RIPPER) individual rules to make them work better together. In contrast, this paper shows how good rule sets can be learned one rule at a time, without any need for global...

A sequential rule expresses a relationship between two series of events happening one after another. Sequential rules are potentially useful for analyzing data in sequential redundant set of sequential rules built upon past work on compact set of representative patterns. A rule is redundant if it can be inferred from another rule having the same support and confidence. When using the set of min...

Data streams are usually characterized by changes in the underlying distribution generating data. Therefore algorithms designed to work with data streams should be able to detect changes and quickly adapt the decision model. Rules are one of the most interpretable and flexible models for data mining prediction tasks. In this paper we present the Adaptive Very Fast Decision Rules (AVFDR), an on-...

In support of reasoning with sparse rule bases, fuzzy rule interpolation (FRI) offers a helpful inference mechanism for deriving an approximate conclusion when a given observation has no overlap with any rule in the existing rule base. One of the recent and popular FRI approaches is the scale and move transformation-based rule interpolation, known as T-FRI in the literature. It supports both in...

The promise of rule-based computing was to allow end users to create, modify, and maintain applications without the need to engage programmers. But experience has shown that rule sets often interact in subtle ways, making them difficult to understand and reason about. This has impeded the wide-spread adoption of rule-based computing. This paper describes the design and implementation of XcelLog...

Article history: Received 15 February 2005 Received in revised form 29 July 2005 Accepted 9 August 2005 This paper presents a hybrid evolutionary algorithm (HEA) to discover complex rule sets predicting the concentration of chlorophyll-a (Chl.a) based on themeasuredmeteorological, hydrological and limnological variables in the hypertrophic Nakdong River. The HEA is designed: (1) to evolve the s...

This paper presents some highlights in the application of neural networks, fuzzy logic, genetic algorithms, and rough sets to automated knowledge acquisition. These techniques are capable of dealing with inexact and imprecise problem domains and have been demonstrated to be useful in the solution of classification problems. It addresses the issue of the application of appropriate evaluation cri...