Duruma özgü aktarılabilir inanç modeli ile örüntü sınıflandırma uygulaması

In this thesis, a classifier based on the Transferable Belief Model is implemented to classify warships automatically according to their type. The classifier is called as the Case Based Classifier. Uncertainty was assumed to exist in the measurements obtained from the sensors that provide data to the classifier. The Transferable Belief Model is more successful in modelling this uncertainty than the conventional methods such as Bayesian Theory and Fuzzy Set Theory. In addition, the Transferable Belief Model allows the fusion of information coming from different sensors it can detect any conflict that may exist among the measurements obtained from different sensors. Classification performance of the case-based classifier was identified on an artificial database and it was shown to be applicable to real-world problems.