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Research on investment portfolio model based on neural network and genetic algorithm in big data era
EURASIP Journal on Wireless Communications and Networking ( IF 2.6 ) Pub Date : 2020-11-02 , DOI: 10.1186/s13638-020-01850-x
Wei Zhou , Yuanjun Zhao , Weiwei Chen , Yanghui Liu , Rongjun Yang , Zheng Liu

With the maturity of neural network theory, it provides new ideas and methods for the prediction and analysis of stock market investment. The purpose of this paper is to improve the accuracy of stock market investment prediction, we build neural network model and genetic algorithm model, study the law of stock market operation, and improve the effectiveness of neural network and genetic algorithm. Through the empirical research, it is found that the neural network model can make up for the shortcomings of the traditional algorithm through the optimization of genetic algorithm.



中文翻译:

大数据时代基于神经网络和遗传算法的投资组合模型研究

随着神经网络理论的成熟,它为股票市场投资的预测和分析提供了新的思路和方法。本文的目的是提高股票市场投资预测的准确性,建立神经网络模型和遗传算法模型,研究股票市场运作规律,提高神经网络和遗传算法的有效性。通过实证研究,发现神经网络模型可以通过遗传算法的优化来弥补传统算法的不足。

更新日期:2020-11-03
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