1 - 6 of 6 articles
In many data mining applications, the objective is to select data cases of a target class. For example, in direct marketing, marketers want to select likely buyers of a particular product for promotion. In such applications, it is often too difficult to predict who will definitely be in the...
A framework for hybridizing evolutionary algorithms with the branch-and-bound algorithm (B&B) is presented in this paper. This framework is based on using B&B as an operator embedded in the evolutionary algorithm. The resulting hybrid operator will intelligently explore the dynastic potential...
This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers dedicated to the control of heating, ventilating and air conditioning systems concerning energy performance and indoor comfort requirements. This problem has some specific restrictions that make it...
In real applications, data provided to a learning system usually contain linguistic information which greatly influences concept descriptions derived by conventional inductive learning methods. Design of learning methods for working with vague data is thus very important. In this paper, we apply...
The present article concerns neural based image processing and solutions developed for industrial problems using the ZISC-036 neuro-processor, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm (RCE) and the K-Nearest Neighbor algorithm (KNN). The developed neural...
Identifying interesting changes from a sequence of overhead imagery—as opposed to clutter, lighting/seasonal changes, etc.—has been a problem for some time. Recent advances in data mining have greatly increased the size of datasets that can be attacked with pattern discovery methods. This paper...
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