基于模糊神经网络算法预测电价数据分析  

Predicting Electricity Price Data Based on Fuzzy Neural Network Algorithm

作　　者：郑雅姣 李享蔚 Zheng Yajiao;Li Xiangwei(School of Electrical and Control Engineering,Liaoning Technical University,Huludao Liaoning 125105,China)

机构地区：[1]辽宁工程技术大学电气与控制工程学院,辽宁葫芦岛125105

出　　处：《现代工业经济和信息化》2024年第7期264-266,共3页Modern Industrial Economy and Informationization

摘　　要：由于实时电价具有很强的波动性,它受到的干扰因素较大,很难实现能量的合理调度[1],因此提出一种基于模糊神经网络算法(Fuzzy Neural Network,FNN)的电价数据预测。对电价数据预测的问题和挑战进行一系列分析,并对模糊神经网络算法进行概述,将模糊神经网络算法应用于电价数据预测中,并进行实验设计与结果分析。通过系统测试实验得出结论:应用模糊神经网络算法可以提高预测电价数据的准确性。Due to the strong volatility of real-time electricity price,it is subject to large disturbing factors,which makes it difficult to realize the rational dispatch of energy,[1]so a fuzzy neural network(FNN)based algorithm is proposed to predict the electricity price data.In this paper,a series of problems and challenges of electricity price data prediction are analyzed and an overview of the fuzzy neural network algorithm is given,the fuzzy neural network algorithm is applied to electricity price data prediction,and experimental design and results are analyzed.Through the system testing experiments,it is concluded that the application of fuzzy neural network algorithm can improve the accuracy of predicting electricity price data.

关 键 词：神经网络 建模分析 电价数据预测 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]