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This paper studies a distributed dynamic resource allocation problem for a multi-agent network with a strongly connected digraph, which has increased an equality constraint for individual node requirement from the point of dynamic prediction horizon. Each agent at each prediction horizon in the network is associated with a local resource and a quadratic convex cost function. The goal is to minimize...
In this paper, a novel data driven knowledge extraction scheme is proposed and applied to realize power system stability estimation since power system stability assessment can be treated as a typical classification problem (stable/unstable). The strategy is composed of three cascading layers, including the feature selection for choosing an optimal subset from candidate inputs, pattern discovery layer...
In order to reduce the time of neural network self-learning, it proposes an algorithm which combines genetic algorithm (GA) and neural network prediction together. Genetic algorithm is used to search the optimal solution globally, and the data generated by GA during evolutionary process are used to train a predictive network. The predictive network establishes a mapping between parameters of operant...
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