Case-based reasoning system for predicting yarn tenacity

摘要

Case-based reasoning (CBR) is an advanced reasoning technique simulating how hu mans routinely solve problems. There are several steps in CBR: presentation of a new problem, retrieval of the most similar cases from the database of cases, adaptation of the most similar old solutions, validation of the current solution, and updating of the system by adding the verified solution to the database of cases. This study briefly demonstrates how CBR provides a new and alternative approach for understanding the complex rela tionships between fiber properties and predicting their influences on the resulting yarn qualities. This investigation reveals that CBR is sufficiently transparent for spinners to understand how the yarn strength of a particular cotton sample is derived.