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A PRACTICAL AND FLEXIBLE ENVIRONMENT FOR ADAPTIVE KNOWLEDGE AND DATA FUSION APPLICATIONS.

By David Tuck and Sensing Team

Abstract

The purpose of this paper is to describe and demonstrate a new approach for a practical and flexible environment for implementing knowledge and data fusion applications. Data fusion is used today in many engineering and managerial applications to help resolve complex planning, control and optimisation problems. A time-series application case study is presented and discussed: a prototype robot arm control example, utilising a fuzzy neural network (FuNN) tool module for off-line learning and rule manipulation, and a new on-line evolving fuzzy neural network (EFuNN) adapting tool module, from this environment. 1

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.134.8942
Provided by: CiteSeerX
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