Developing multi-agent systems with a FIPA-compliant agent framework
Software—Practice & Experience
Past, present, and future of decision support technology
Decision Support Systems - Special issue: Decision support systems: Directions for the next decade
Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications
Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications
The dMARS Architecture: A Specification of the Distributed Multi-Agent Reasoning System
Autonomous Agents and Multi-Agent Systems
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A process model to develop an internal rating system: sovereign credit ratings
Decision Support Systems
A metadatabase-enabled executive information system (part A): a flexible and adaptable architecture
Decision Support Systems
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
ODDM: A framework for modelbases
Decision Support Systems
Expert Systems with Applications: An International Journal
Early warning systems for sovereign debt crises: The role of heterogeneity
Computational Statistics & Data Analysis
Business analytics in supply chains - The contingent effect of business process maturity
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
For the successful probability of default (PD) evaluation with the application of multiple prediction models two issues should be addressed: the accuracy of the analytic models which decreases over time and the evaluation of results which must be presented in a uniform shape. To deal with these two issues, a multi-agent system (MAS) and knowledge management systems (KMS) based process management system is proposed. The proposed system has two goals: to prevent the PD information quality deterioration by active management of analytical processes and to provide a universal access point allowing the simultaneous use of multiple prediction models.