Structural Reliability Through Machine Learning From Case Histories

by John R. Stone, Univ of Bristol, United Kingdom,
David I. Blockley, Univ of Bristol, United Kingdom,

Document Type: Proceeding Paper

Part of: Structural Safety and Reliability


The development of a management tool for the control of structural safety is described. Artificial intelligence techniques of 'machine learning' are employed to facilitate a method of learning from past experience. The serial and parallel approaches of discrimination and connectivity analysis are employed. A technique for building a hierarchically structured knowledge base made up from the study of individual case histories is outlined. Support logic is used to permit an 'open world' representation of uncertainty.

Subject Headings: Structural reliability | Case studies | Equipment and machinery | Artificial intelligence | Structural safety | Structural systems | Structural analysis | Failure analysis

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