标题： LSTM、GRU和Transformer模型在股票价格预测中的比较分析 显示英文标题

标题： Comparative Analysis of LSTM, GRU, and Transformer Models for Stock Price Prediction

摘要： 在近期节奏快速的金融市场中，投资者不断寻求方法以获得优势并做出明智决策。尽管在股票价格预测方面实现完全准确仍然难以达到，但人工智能（AI）的发展显著提升了我们分析历史数据和识别潜在趋势的能力。本文以AI驱动的股票价格趋势预测为核心研究内容，制作了从2015年到2024年著名特斯拉汽车公司的模型训练数据集，并比较了LSTM、GRU和Transformer模型。分析更加符合股票趋势预测模型，实验结果显示LSTM模型的准确率为94%。这些方法最终使投资者能够做出更明智的决策，并更清晰地洞察市场行为。 显示英文摘要

摘要： In recent fast-paced financial markets, investors constantly seek ways to gain an edge and make informed decisions. Although achieving perfect accuracy in stock price predictions remains elusive, artificial intelligence (AI) advancements have significantly enhanced our ability to analyze historical data and identify potential trends. This paper takes AI driven stock price trend prediction as the core research, makes a model training data set of famous Tesla cars from 2015 to 2024, and compares LSTM, GRU, and Transformer Models. The analysis is more consistent with the model of stock trend prediction, and the experimental results show that the accuracy of the LSTM model is 94%. These methods ultimately allow investors to make more informed decisions and gain a clearer insight into market behaviors.