Hybrid models in agent-based environmental decision support
Providing informational support in decision making is one of the priority directions of research in the sphere of public health management. Modern approaches suggest wide usage of intelligent data mining methods and Web-services, but just a few enable to study a complex system from an interdisciplinary point of view. In this paper an agent-based decision support system (ADSS), which embodies the principles of the interdisciplinary approach and facilitates multi-focal view and examination of the EnvironmentPublic health system, is introduced. The detailed design of the system with the emphasis on the roles, scenarios and its implementation is presented. The data mining procedures used for data preparation, modeling and simulation, which include statistics, methods of artificial intelligence and hybrid models in form of cascade committee machines, are described. Then, the advantages of the proposed hybrid models against singular modeling methods are demonstrated. Finally, a case study for a selected region is presented and its results are discussed.
hybrid models decision support systems simulation human health environmental pollution multi-agent systems