A composite approach to inducing knowledge for expert systems design

Article Abstract:

The Composite Rule Induction System (CRIS) is a new approach to the knowledge acquisition problem in expert systems design. The CRIS relies on inductive inference methods to obtain the decision rules that determine the decision-making capabilities of expert systems. The central idea underlying this approach is that the characteristics of nonnominal and nominal attributes need to be analyzed separately to induce decision rules from the data obtained from human experts. The CRIS approach is observed to have greater predictive ability compared to other inductive inference methods such as ACLS, PLS1 and discriminant analysis.

Research, Expert systems, Inductive reasoning, Induction (Logic), Knowledge acquisition (Expert systems)

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Burn-in time and estimation of change-point and Weibull-exponential mixture distribution

Article Abstract:

Two cost models are developed to estimate the optimal burn-in time of products to identify early failures before shipment at minimum per-item expected cost. A Weibull-exponential distribution was used as a product life distribution model. Results show that, for both repairable and non-repairable products, burn-in time should not exceed that of the change-point, which can be estimated by the maximum-likelihood method.

Models, Reports, Cost benefit analysis, Burn-in testing

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