The top-down approach is based on running the recursive code as is, generating implicitly the recursion structure from the root of the DAG down to the leaves. Each time a solution to a smaller instance is found for the first time it generates a mapping from the input argument to its solution. This way when we come across the same argument a second time we can just look up the solution. This pro...

The application of neural networks technology to dynamic system control has been constrained by the non-dynamic nature of popular network architectures. Many of difficulties are-large network sizes (i.e. curse of dimensionality), long training times, etc. These problems can be overcome with dynamic neural networks (DNN). In this study, intelligent optimal control problem is considered as a nonl...

We introduce the structural interface algorithm for exact probabilistic inference in dynamic Bayesian networks. It unifies state-of-the-art techniques for inference in static and dynamic networks, by combining principles of knowledge compilation with the interface algorithm. The resulting algorithm not only exploits the repeated structure in the network, but also the local structure, including ...

Data warehouses (DW) are an emerging technology to support high-level decision making by gathering information from several distributed information sources (ISs) into one materialized repository. In dynamic environments such as the web, DWs must be maintained in order to stay up-to-date. Recent maintenance algorithms tackle this problem of DW management under concurrent data updates (DU), where...