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Data Driven Knowledge Extraction of Materials Properties

Kandola, J.S., Gunn, S.R., Sinclair, I. and Reed, P.A.S. (1999) Data Driven Knowledge Extraction of Materials Properties At Intelligent Processing and Manufacturing of Materials. , pp. 361-366.

Record type: Conference or Workshop Item (Other)


In this paper the problem of modelling a large commercial materials dataset using advanced adaptive numeric methods is described. The various approaches are briefly outlined, with an emphasis on their characteristics with respect to generalisation, performance and transparency. A highly novel Support Vector Machine (SVM) approach incorporating a high degree of transparency via a full ANalysis Of VAriance (ANOVA) expansion is also used. Using the example of predicting 0.2% proof stress from a set of materials features, we show how the different modelling techniques compare when benchmarked against independent test data.

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Published date: July 1999
Additional Information: Accepted for Publication at IPMM 99 CD-ROM. Organisation: IEEE
Venue - Dates: Intelligent Processing and Manufacturing of Materials, 1999-07-01
Organisations: Electronic & Software Systems


Local EPrints ID: 252054
PURE UUID: 90d90a25-d044-4e2c-b731-03da09dc10c7

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Date deposited: 29 Nov 2003
Last modified: 18 Jul 2017 10:07

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Author: J.S. Kandola
Author: S.R. Gunn
Author: I. Sinclair
Author: P.A.S. Reed

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