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Predicting Consumer Behavior with Artificial Neural Networks

机译：预测人工神经网络的消费者行为

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摘要

Nowadays facile access to information and advancements in processing power unfold opportunities for new decision suDDOrt techniques used for financial and economic purposes. Artificial neural networks are machine learning techniques which integrate a series of features upholding their use in financial and economic applications. Backed up by flexibility in dealing with various types of data and high accuracy in making predictions, these techniques bring substantial benefits to husiness activities. This paper investigates how consumer behavior can be identified using artificial neural networks, based on information obtained from traditional surveys. Results highlight that neural networks have a good discriminatory power, generally providing better results compared with traditional discriminant analysis.
机译：如今，可以进入处理电力展开机会的信息和进步，用于新决定的仓库技术用于金融和经济目的。人工神经网络是机器学习技术，它集成了一系列拥有在金融和经济应用中使用的功能。通过灵活性地处理各种类型的数据和高精度，在制定预测方面，这些技术为大海育活动带来了大量的益处。本文研究了根据传统调查获得的信息如何使用人工神经网络识别消费者行为。结果强调神经网络具有良好的歧视性，通常提供更好的结果与传统的判别分析相比。

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