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Emotional Temporal Difference Learning Based Multi-layer Perceptron Neural Network Application to a Prediction of Solar Activity

机译:基于情感时差学习的多层感知器神经网络在太阳活动预测中的应用

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Nonlinear time series prediction has in recent years, been the subjects of many methodological and applied studies in the fields of system identification and nonlinear prediction. An important benchmark has been the prediction of solar activity with the markup increase in the practical importance of space weather forecasting; its motivation has risen far beyond more methodological concerns. In this paper, we have used a bounded rationality decision-making procedure, whose utility has been demonstrated in several identification and control tasks, for predicting sunspot numbers. An emotional temporal difference learning based multi layer perceptron neural network is introduced and applied to the prediction task.
机译:近年来,非线性时间序列预测已成为系统识别和非线性预测领域中许多方法学和应用研究的主题。一个重要的基准是随着空间天气预报的实际重要性的增加,对太阳活动的预测。它的动机已经远远超出了方法论上的关注。在本文中,我们使用了有限理性决策程序来预测黑子数,该决策程序的有效性已在多个识别和控制任务中得到证明。介绍了一种基于情感时差学习的多层感知器神经网络,并将其应用于预测任务。

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