Combining back-propagation and genetic algorithms to train neural networks for start-up time modeling in combined cycle power plants

نویسندگان

  • Ilaria Bertini
  • Matteo De Felice
  • Stefano Pizzuti
چکیده

This paper presents a neural networks based approach in order to estimate the start-up time of turbine based power plants. Neural networks are trained with a hybrid approach, indeed we combine the Back-Propagation (BP) algorithm and the Simple Genetic Algorithm (GA) in order to effectively train neural networks in such a way that the BP algorithm initializes a few individuals of the GA's population. Experiments have been performed over a big amount of data and results have shown a remarkable improvement in accuracy compared to the single traditional methods.

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تاریخ انتشار 2010