A Proposed Model Of Neural Network For Rupiah Exchange Rate’s Prediction

Primandani Arsi, Oman Somantri, U. Hasanah, Tri Astuti, Mohammad Imron, Retno Waluyo
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引用次数: 1

Abstract

Exchange rates are the value of a foreign currency against a domestic currency. Exchange rates and international trade are two interrelated things. One of the obstacles in international trade activities is due to differences in exchange rates. Exchange rate fluctuations occur every day and are uncertain. For business people, exchange rate uncertainty creates problems that affect losses in their business. Therefore, a prediction is needed to estimate the future exchange rate. In this study, rupiah exchange rate data is used to build a prediction model of the rupiah exchange rate against the dollar (US). The experimental results state that the neural network obtained RMSE results of 0.010 +/− 0.001.
印尼盾汇率预测的神经网络模型
汇率是指外国货币对本国货币的价值。汇率和国际贸易是两件相互关联的事情。国际贸易活动的障碍之一是由于汇率的差异。汇率每天都在波动,而且不确定。对于商人来说,汇率的不确定性会造成影响他们生意损失的问题。因此,需要对未来的汇率进行预测。本研究使用印尼盾汇率数据建立印尼盾对美元汇率的预测模型。实验结果表明,神经网络得到的RMSE结果为0.010 +/−0.001。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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