Yagi, H. Primary Author mixed material bibliography Taylor & Francis 2012 id Indonesia

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In this study, the acquisition of rule-type knowledge from field inspection data on highway bridges is enhanced by introducing an improvement to a traditional data mining technique, i.e. applying the rough set theory to the traditional decision table reduction method. The new rough set theory approach helps in cases of exceptional and contradictory data, which in the traditional decision table reduction method are simply removed from analyses. Instead of automatically removing all apparently contradictory data cases, the new method determines whether the data really is contradictory and therefore must be removed or not. The new method is tested with real data on bridge members including girders and filled joints in bridges owned and managed by a highway corporation in Japan. There are, however, numerous inconsistent data in field data. A new method is therefore proposed to solve the problem of data loss. The new method reveals some generally unrecognized decision rules in addition to generally accepted knowledge. Finally, a computer programs is developed to perform calculation routines, and some field inspection data on highway bridges is used to show the applicability of the proposed method. BRIDGES 624.21(063) Perpustakaan Direktorat Bina Teknik Jalan dan Jembatan Direktorat Jenderal Bina Marga - Kementerian Pekerjaan Umum (NPP: 3273244A00000001) 0000020756 My Library 20033 machine generated