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2 2011

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Towards a case-based computational model for the creative design of electromagnetic devices

Ouyang J., Lowther D.

Archives of Electrical Engineering

2011

Vol. 60, nr 4

485-496

In order to explore creativity in design, a computational model based on Case-Based Reasoning (CBR) (an approach to employing old experiences to solve new problems) and other soft computing techniques from machine learning, is proposed in this paper. The new model is able to address the four challenging issues: generation of a design prototype from incomplete requirements, judgment and improvement of system performance given a sparse initial case base library, extraction of critical features from a given feature space, adaptation of retrieved previous solutions to similar problems for deriving a solution to a given design task. The core principle within this model is that different knowledge from various level cases can be explicitly explored and integrated into a practical design process. In order to demonstrate the practical significance of our presented computational model, a case-based design system for EM devices, which is capable of deriving a new design prototype from a real-world device case base with high dimensionality, has been developed.

A novel adaptation approach for electromagnetic device optimization

Ouyang J., Lowther D.

Archives of Electrical Engineering

2011

Vol. 60, nr 4

473-483

The ability of case-based reasoning systems to solve new problems mainly depends on their case adaptation knowledge and adaptation strategies. In order to carry out a successful case adaptation in our case-based reasoning system for a low frequency electromagnetic device design, we make use of semantic networks to organize related domain knowledge, and then construct a rule-based inference system which is based on the network. Furthermore, based on the inference system, a novel adaptation algorithm is proposed to derive a new device case from a real-world induction motor case-base with high dimensionality.