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Artificial neural network application in modeling revenue returns from mobile payment services in Kenya

机译:人工神经网络在肯尼亚移动支付服务收益建模中的应用

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Artificial Neural Networks has recently shown a great applicability in time-series analysis and forecasting thus correctly deducing the unseen part of the population even if the sample data contain noisy information. In this paper we used Neural Network to model revenue returns from mobile payment services using dataset extracted from Central Bank of Kenya website. The network with one or two hidden layers was tested with various combination of neurons, and results were compared in terms of forecasting error. It was observed that ANN if properly trained accurately forecast Revenue returns on mobile payments services in Kenya.
机译:人工神经网络最近在时间序列分析和预测中显示出巨大的适用性,因此即使样本数据包含嘈杂的信息,也可以正确推断出人口中看不见的部分。在本文中,我们使用神经网络使用从肯尼亚中央银行网站提取的数据集对移动支付服务的收益回报进行建模。用各种神经元组合测试具有一或两个隐藏层的网络,并根据预测误差比较结果。据观察,如果经过适当培训,人工神经网络将准确预测肯尼亚移动支付服务的收益回报。

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