.png){kind=icon}
返回
Effective long short-term memory with fruit fly optimization algorithm for time series forecasting
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-020-04855-2.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A number of recent studies have adopted long short-term memory (LSTM) in extensive applications, such as handwriting recognition and time series prediction, with considerable success. However, the parameters of LSTM have greatly influenced its accuracy and performance. In this study, LSTM with fruit fly optimization algorithm (FOA), called FOA-LSTM, is designed to solve time series problems. As a novel intelligent algorithm, FOA is applied to decide on the optimal hyper-parameter of LSTM. Experiments under the NN3 time series, three comparative experiments and the monthly energy consumption of the USA are conducted to verify the effectiveness of the FOA-LSTM model. The results indicate that the symmetric mean absolute percentage error (SMAPE) is reduced by up to 11.44% in the last 11 monthly series in the NN3 dataset. Four comparative experiments and the real-life series verify further that the FOA-LSTM model obtains a better result compared with other forecasting models.
Keyword:
Long short-term memory
Fruit fly optimization algorithm
Time series forecasting
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
Effective long short-term memory with differential evolution algorithm for electricity price prediction基于差分进化算法的长短期记忆电价预测.png)
ENERGY
ENERGYIF9.4
PREAI
分享收藏Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms预测现货电价: 深度学习方法和传统算法的实证比较APPLIED ENERGY
OAAI
APPLIED ENERGYIF11
OAAI分享收藏Support vector regression with fruit fly optimization algorithm for seasonal electricity consumption forecasting基于果蝇优化的支持向量回归季节性用电量预测ENERGY
ENERGYIF9.4
PREAI
分享收藏Multi-objective evolutionary feature selection for online sales forecasting在线销售预测的多目标进化特征选择NEUROCOMPUTINGOAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network基于增强型反向传播神经网络的多因素影响能耗预测ENERGY
ENERGYIF9.4
PREAI
分享收藏Fruit fly optimization algorithm based fractional order fuzzy-PID controller for electronic throttle
PREAI
分享收藏δ-agree AdaBoost stacked autoencoder for short-term traffic flow forecastingNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏A new Fruit Fly Optimization Algorithm: Taking the financial distress model as an example一种新的果蝇优化算法 -- 以财务困境模型为例
PREAI
分享收藏
查看更多内容