摘 要
本文以基于深度学习的电力需求预测算法研究为研究题目，探讨了电力需求预测的基本理论、评价指标和方法。在此基础上，本文详细阐述了基于深度学习的电力需求预测模型建立、算法设计及实现和测试。同时，介绍了深度学习在电力需求预测中的三种应用方式，即时间序列预测方法、自然语言处理技术以及神经网络。研究结果表明，基于深度学习的算法能够有效提高电力需求预测的准确性和实用性，为电力行业的管理和发展提供了一定的参考。
关键词：深度学习、电力需求预测、时间序列预测、自然语言处理技术、神经网络
Abstract
This article focuses on the research of power demand prediction algorithms based on deep learning, and explores the basic theories, evaluation indicators, and methods of power demand prediction. On this basis, this article elaborates in detail on the establishment, algorithm design, implementation, and testing of a power demand prediction model based on deep learning. At the same time, three application modes of deep learning in power demand forecasting are introduced, which are time series forecasting method, natural language processing technology and neural network. The research results indicate that algorithms based on deep learning can effectively improve the accuracy and practicality of power demand prediction, providing a certain reference for the management and development of the power industry.
Keyword: Deep learning、power demand forecasting、time series forecasting、 natural language processing technology、neural network
目 录
1引言 1
2电力需求预测理论基础 2
2.1电力需求预测的基本方法和模型 2
2.2深度学习在电力需求预测中的应用 3
2.3电力需求预测的评价指标和方法 4
3基于深度学习的电力需求预测算法研究 4
3.1基于深度学习的电力需求预测模型建立 4
3.2基于深度学习的电力需求预测算法设计 5
3.3基于深度学习的电力需求预测系统实现和测试 5
4深度学习在电力需求预测中的应用 6
4.1时间序列预测方法 6
4.2自然语言处理技术在电力需求预测中的应用 6
4.3神经网络在电力需求预测中的应用 7
5结语 8
参考文献 9
致谢 10
本文以基于深度学习的电力需求预测算法研究为研究题目，探讨了电力需求预测的基本理论、评价指标和方法。在此基础上，本文详细阐述了基于深度学习的电力需求预测模型建立、算法设计及实现和测试。同时，介绍了深度学习在电力需求预测中的三种应用方式，即时间序列预测方法、自然语言处理技术以及神经网络。研究结果表明，基于深度学习的算法能够有效提高电力需求预测的准确性和实用性，为电力行业的管理和发展提供了一定的参考。
关键词：深度学习、电力需求预测、时间序列预测、自然语言处理技术、神经网络
Abstract
This article focuses on the research of power demand prediction algorithms based on deep learning, and explores the basic theories, evaluation indicators, and methods of power demand prediction. On this basis, this article elaborates in detail on the establishment, algorithm design, implementation, and testing of a power demand prediction model based on deep learning. At the same time, three application modes of deep learning in power demand forecasting are introduced, which are time series forecasting method, natural language processing technology and neural network. The research results indicate that algorithms based on deep learning can effectively improve the accuracy and practicality of power demand prediction, providing a certain reference for the management and development of the power industry.
Keyword: Deep learning、power demand forecasting、time series forecasting、 natural language processing technology、neural network
目 录
1引言 1
2电力需求预测理论基础 2
2.1电力需求预测的基本方法和模型 2
2.2深度学习在电力需求预测中的应用 3
2.3电力需求预测的评价指标和方法 4
3基于深度学习的电力需求预测算法研究 4
3.1基于深度学习的电力需求预测模型建立 4
3.2基于深度学习的电力需求预测算法设计 5
3.3基于深度学习的电力需求预测系统实现和测试 5
4深度学习在电力需求预测中的应用 6
4.1时间序列预测方法 6
4.2自然语言处理技术在电力需求预测中的应用 6
4.3神经网络在电力需求预测中的应用 7
5结语 8
参考文献 9
致谢 10
