This article aims to design a self-organizing decision support system for early detection of important physiological events. The proposed consists pre-processing, clustering and diagnostic systems based on fuzzy logic modelling. Clustering methods have been used in empirical pattern analysis. Especially when the available information is incomplete or data model subject ambiguity. applies primar...

The authors illustrate several issues in decision support and decision support systems (DSS), state of the art research in these fields, and also their own studies in designing a higher education DSS. The final section contains our contribution in outlining the modules of the DSS, involving the present systems and databases of FSEGA and UBB, results and activities belonging to FSEGA students, t...

This study presents a novel risk-based decision support system for helping disaster risk management planners select the best locations emergency shelters after an earthquake. The starts by identifying 18 criteria, based on stakeholder analysis, that are important selecting shelter sites. These criteria then standardized to reflect their importance in site selection process. Next, Large Group De...

The healthcare industry collects huge amounts of data which, unfortunately, are not turned into useful information for effective decision making. Decision support systems (DSS) can now use advanced technologies such as On-Line Analytical Processing (OLAP) and data mining to deliver advanced capabilities. This paper presents a prototype clinical decision support system which combines the strengt...