Shauharda Khadka

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Ever increasing energy demands are driving the development of high-efficiency power generation technologies such as direct-fired fuel cell turbine hybrid systems. Due to lack of an accurate system model, high nonlinearities and high coupling between system parameters, traditional control strategies are often inadequate. To resolve this problem, learning(More)
In this paper, we present a new memory-augmented neural network called Gated Recurrent Unit with Memory Block (GRU-MB). Our architecture builds on the gated neural architecture of a Gated Recurrent Unit (GRU) and integrates an external memory block, similar to a Neural Turing Machine (NTM). GRU-MB interacts with the memory block using independent read and(More)
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