Neural networks through stock market data prediction

Rohit Verma, Pkumar Choure, Upendra Singh
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引用次数: 25

Abstract

In the proposed work, we presented an Artificial Neural Network approach to predict the stock market indices. We outlined the design of the Neural Network model with its salient features and customizable parameters. A number of the activation functions are implemented along with the options for the cross validation sets. We finally test our algorithm on the Nifty stock index dataset where we predict the values on the basis of values from the past days. We achieve a best case accuracy of 96% on the dataset.
神经网络通过股票市场数据预测
在本文中,我们提出了一种人工神经网络方法来预测股票市场指数。我们概述了神经网络模型的设计及其显著特征和可定制的参数。许多激活函数与交叉验证集的选项一起实现。最后,我们在Nifty股票指数数据集上测试了我们的算法,我们根据过去几天的值来预测值。我们在数据集上实现了96%的最佳案例准确率。
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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