.png){kind=icon}
返回
Variable frequency wind speed trend prediction system based on combined neural network and improved multi-objective optimization algorithm
.png){kind=icon}
PRE
AI
DOI：10.1016/j.energy.2022.124249.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Trend prediction data with low measurement frequency has always been needed in wind power station, but the traditional multi-step prediction method has caused error accumulation and led to poor prediction accuracy, in order to solve this problem, a new wind speed trend prediction system is proposed which includes data preprocessing (Fuzzy Information Granulation), combined neural network prediction and an improved multi-objective manta rays foraging optimization based on Tent chaotic map and T-distribution perturbation operator (IMOMRFO). The algorithm not only has a good ability to escape from the local optimal solution, but also proves theoretically that the Pareto optimal solution is obtained. Through the simulation of four groups of experiments, it is obvious that the stability, generalization and accuracy of the model are satisfactory. It is confirmed that the model greatly improves the accuracy of trend prediction and makes a certain contribution to solve the problem of wind speed prediction, through the test of the ability of point prediction and interval prediction of the model. (c) 2022 Elsevier Ltd. All rights reserved.
Keyword:
Wind speed prediction
Fuzzy information granulation
Combined neural network
Improved multi-objective optimization
期刊
IF:
9.4
论文数:
4.3W
被引数:
20.2W
机构
暂无机构信息
引用论文
A novel combined model for wind speed prediction - Combination of linear model, shallow neural networks, and deep learning approaches.png)
ENERGY
ENERGYIF9.4
PREAI
分享收藏Evaluation of the US department of energy's weatherization assistance program: Impact resultsENERGY POLICY
OAAI
ENERGY POLICYIF9.2
OAAI分享收藏MLP-BP: A novel framework for cuffless blood pressure measurement with PPG and ECG signals based on MLP-Mixer neural networksMlp-bp: 基于mlp-mixer神经网络的PPG和ECG信号无袖带血压测量的新框架
PREAI
分享收藏Robust image watermarking using invariant accurate polar harmonic Fourier moments and chaotic mappingSIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏Lithium-ion battery state-of-charge estimation for small target sample sets using the improved GRU-based transfer learning基于改进GRU迁移学习的小目标样本集锂离子电池荷电状态估计ENERGY
ENERGYIF9.4
PREAI
分享收藏
查看更多内容