A Comparative Study of Evolutionary Algorithms for Training Elman Recurrent Neural Networks to Predict Autonomous Indebtedness
نویسندگان
چکیده
This paper presents a training model for Elman recurrent neural networks, based on evolutionary algorithms. The proposed evolutionary algorithms are classic genetic algorithms, the multimodal clearing algorithm and the CHC algorithm. These training algorithms are compared in order to assess the effectiveness of each training model when predicting Spanish autonomous indebtedness.
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