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Indian Currency Exchange Rate Forecasting Using Neural Networks

机译:神经网络的印度货币汇率预测

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Predicting currency exchange rate and handling enormous data with traditional time series analysis has proven to be difficult An artificial neural network may be more suitable for the task because no assumption about a suitable mathematical model has to be made prior to forecasting and being a stochastic method it can reach the near optimum solution in relatively lesser time. Furthermore, a neural network has the ability to extract useful information from large sets of data, which is required for a satisfying description of a financial time series. This paper discusses the various conventional analysis methods and neural network methodology to forecast the currency exchange rate. The paper also provides the effects of various topological parameters on the accuracy and training time of neural networks. A topology of neural network is proposed for the prediction of Indian currency exchange rate.
机译:事实证明,使用传统的时间序列分析来预测货币汇率并处理大量数据非常困难。人工神经网络可能更适合于此任务,因为在进行预测并将其作为一种随机方法之前,无需对合适的数学模型进行任何假设即可。可以在相对较短的时间内达到接近最佳的解决方案。此外,神经网络具有从大量数据中提取有用信息的能力,这对于满足财务时间序列的描述是必需的。本文讨论了预测货币汇率的各种常规分析方法和神经网络方法。本文还提供了各种拓扑参数对神经网络的准确性和训练时间的影响。提出了一种神经网络拓扑结构,用于预测印度货币汇率。

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