• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.308-313
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• 1998

In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general description of concepts from specific instances of these concepts. In many real life situations, however, new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overcall set of instances. The method of learning presented here is base don a rough set concept proposed by Pawlak[2][11]. It is shown an algorithm to find minimal set of rules using reduct change theorems giving criteria for minimum recalculation with an illustrative example. Finally, the proposed learning algorithm is applied to fuzzy system to learn sampled I/O data.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.69-76
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• 1994

Thermal elasto-plastic analysis of axi-symmetric body by the finite element method is presented in this paper for analyzing the process of upset forming of circular section extruded bar. The example of calculation for upset forming of Nimonic extruded bar is also presented. It is shown that remeshing of quadrilateral finite element is necessary because the very highly distorted element by plastic deformation disturbs the calculation. Calculated values for nodal points in new mesh are obtained from nodal points of old mesh by linear interpolation method. The experimental results are compared with calculated values. The appearance of upsetupset forming obtained by experimental method is very similar to that obtained by calculations. So, it is proved that the thermal elasto-plastic analysis of axi-symmetric body by the finite element method is very useful for finding the optimum upsetting condition.