We will select a development platform that is multithreaded, distributed, object-oriented, and has a rich set of predefined class libraries. This strategy will minimize the amount of effort devoted to server implementation and maximize the resources available to the interface module and to the subsystems models. Simpler physics-based models will be derived or existing models improved, based on subsystem modeling results. In this way, simplifying assumptions and parameterizations inherent in the high-level models can be tested. Neural nets, adaptive learning systems that mathematically develop relationships between data sets, will be designed from large data sets produced by the physics-based models.
Neural nets use no physics, only statistical relationships.
We must understand the feedback mechanisms between decision-making tools and science models.