2020 · 13 citations · 3 references
ComputingComputer ScienceFinanceArtificial IntelligenceForecastingMachine LearningFinancial ForecastingForecasting MethodsNeural NetworksTime Series ForecastingTime Series PredictionVolatility ModelingFinancial Time Series ForecastingMachine Learning-based ForecastingMachine Learning-based Price ForecastingNeural ForecastingNeural Network ModelingNeural Network PredictionNeural Time Series ForecastingVolatility
At present, China's economy is undergoing continuous development and progress. With the emergence of new technologies, domestic emerging industries are showing a state of vigorous development, leading to strong volatility in the entire stock market, which brings complex challenges to stock price prediction. Therefore, this paper realizes the judgment of stock price based on artificial neural network and obtains more accurate prediction results. The results of the experiment show that the model proposed in this paper can accurately judge the future price trend of stocks, and the model runs faster, which fundamentally solves the defects of the traditional forecasting methods of slow operation efficiency and low forecast accuracy.
3
Learning Activation Functions to Improve Deep Neural Networks
Forest Agostinelli, Matthew D. Hoffman, Peter Sadowski et al. · arXiv (Cornell University) · 2014 · 350 citations · Full text
Computing, Computer Science, Physics +13