System load trend prediction method based on IF-EMD-LSTM
نویسندگان
چکیده
منابع مشابه
A Threshold Denoising Method Based on Emd
The denoising method based on empirical mode decomposition (EMD) can be broadly divided into: IMF extraction method and IMF threshold approach. Aiming to the problems of how to select IMFs in extraction method and the processing of the selected IMFs, a threshold denoising method based on EMD is put forward. In this method, the standard of IMF selection in energy viewpoint is offered, and the IM...
متن کاملTrend-based load balancer for a distributed Web system
The unexpected and continuous changes of the workload reaching any Internet-based service make really difficult to guarantee a balanced utilization of the server resources. In this paper, we propose a novel class of state-aware dispatching algorithms that take into account not only the present resource load but also the behavioral trend of the server load, that is, whether it is increasing, dec...
متن کاملResearch on PD Signals Denoising Based on EMD Method
Adaptive decomposition of complex data is realized and intrinsic mode function (IMF) components that reflect different scales information are gained through empirical mode decomposition (EMD) of partial discharge (PD) signals. The gained intrinsic mode function components are reconstructed after the wavelet threshold processing to reduce the interference of noise. This partial discharge signals...
متن کاملShort-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation
Accurate load forecasting is an important issue for the reliable and efficient operation of a power system. This study presents a hybrid algorithm that combines similar days (SD) selection, empirical mode decomposition (EMD), and long short-term memory (LSTM) neural networks to construct a prediction model (i.e., SD-EMD-LSTM) for short-term load forecasting. The extreme gradient boosting-based ...
متن کاملA new Prediction method of Gold price: EMD-PSO-SVM
The current gold market shows a high degree of nonlinearity and uncertainty. In order to predict the gold price, Empirical Mode Decomposition (EMD) was introduced into Support vector machine (SVM). Firstly, we used the EMD method to decompose the original gold price series into a finite number of independent intrinsic mode functions (IMFs), and then grouped the IMFs according to different frequ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Distributed Sensor Networks
سال: 2019
ISSN: 1550-1477,1550-1477
DOI: 10.1177/1550147719867655