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原文档可以看这里:Stock Market Analysis + Prediction using LSTM | Kaggle In this notebook, we will discover and explore data from the stock market, particularly some technology stocks (Apple, Amazon, Google, and Microsoft). We will learn how to use yfinance to get stock information, and visual...
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Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies We offer a systematic analysis of the use of deep Park,Frank,C.,... - 《Expert Systems with Application》 被引量: 29发表: 2017年 Predicting Stock Market Trends by Recurrent Deep...
Predicting the trend of stock market prices is a very challenging task, in that stock markets are complicated and can be influenced by a variety of factors. Despite the great difficulty, predicting the trend of stock market prices accurately is very meaningful and can bring a large amount of ...
Stock market trend prediction using ARIMA-based neural networks backpropagation trainingdifference dataWe develop a prediction system useful in forecasting mid-term price trend in Taiwan stock market (Taiwan stock exchange ... JH Wang,JY Leu - IEEE International Conference on Neural Networks 被引量:...
个文件,CHO(包含用于训练神经网络的股票市场数据的数据文件),MATLAB_CODE(.m 文件,这是要在 MATLAB 环境中执行的实际 MATLAB 代码),errperf (删除一些错误的 .m 文件)。所有这些文件都需要存在于同一个文件夹中,一旦 MATLAB_CODE.m 文件被执行,需要选择“添加到路径”,神经网络训练工具打开并epochs(training) ...
The research presented in this work focuses on financial time series prediction problem. The integrated prediction model based on support vector machines (SVM) with independent component analysis (ICA) (called SVM-ICA) is proposed for stock market prediction. The presented approach first uses ICA tec...
1) stock market prediction 股市预测1. This is done by making full use of the advantages of wavelet transform time-frequency localization, the paper proposed an improved wavelet network structure, and considered the model for stock market prediction. 混沌时间序列预测首先要重构相空间 ,接着充分利用...