Computational Intelligence in Multi-Source Data and Information Fusion

Computational Intelligence in Multi-source Data and Information Fusion1

Multi-source Information Fusion Based on Data Driven

Take data driven method as the theoretical basis, study multi-source information fusion technology. Using online and off-line data of the fusion system, does not rely on system's mathematical model, has avoided question about system modeling by mechanism. Uses principal component analysis method, rough set theory, Support Vector Machine(SVM) and so on, three method fusions and supplementary, th...

Multi-source Multi-attribute Data Fusion

A framework for a multi-attribute multi-source data fusion is described. Uncertainty of data is modeled by fuzzy sets. The problem is considered on a general level. Credibility of sources, compatibility of data, as well as their reasonableness, are taken into consideration. The proposed method is illustrated by an example.

Multi-Data Source Fusion in PDMS

In this paper, we propose a new approach for data fusion in the context of schema-based Peer-To-Peer (P2P) systems. Schema-based systems manage and provide query capabilities for (semi-)structured information: queries have to be formulated in terms of schema. The dominating schema-based systems are relational databases or XML documents. Schema-based P2P are called Peer Data Management system (P...

Solution of Evidence Distance in Multi-Source Information Fusion

By relative study on distance measure and conflict evidence synthesis of evidence theory, we find it is very difficult to define strict evidence distance measurement directly. While indirect evidence distance measuring which is based on BPA probability transformation is simple and effective. Current BPA probability transformation methods lack reasonable transformation basis and strong subjectiv...