A novel discrete grey seasonal model and its applications

03/25/2020
by   Weijie Zhou, et al.
0

In order to accurately describe real systems with seasonal disturbances, which normally appear monthly or quarterly cycles, a novel discrete grey seasonal model, abbreviated as , is put forward by incorporating the seasonal dummy variables into the conventional model. Moreover, the mechanism and properties of this proposed model are discussed in depth, revealing the inherent differences from the existing seasonal grey models. For validation and explanation purposes, the proposed model is implemented to describe three actual cases with monthly and quarterly seasonal fluctuations (quarterly wind power production, quarterly PM10, and monthly natural gas consumption), in comparison with five competing models involving grey prediction models , conventional econometric technology , and artificial intelligences . Experimental results from the cases consistently demonstrated that the proposed model significantly outperforms the other benchmark models in terms of several error criteria. Moreover, further discussions about the influences of different sequence lengths on the forecasting performance reveal that the proposed model still performs the best with strong robustness and high reliability in addressing seasonal sequences. In general, the new model is validated to be a powerful and promising methodology for handling sequences with seasonal fluctuations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/19/2019

Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity

Wind energy makes a significant contribution to global power generation....
research
01/04/2022

A new simple dynamic muscle fatigue model and its validation

Musculoskeletal disorder (MSD) is one of the major health problems in ph...
research
08/16/2021

Multistream Graph Attention Networks for Wind Speed Forecasting

Reliable and accurate wind speed prediction has significant impact in ma...
research
08/21/2014

Enhanced Estimation of Autoregressive Wind Power Prediction Model Using Constriction Factor Particle Swarm Optimization

Accurate forecasting is important for cost-effective and efficient monit...
research
11/19/2019

Deep interval prediction model with gradient descend optimization method for short-term wind power prediction

The application of wind power interval prediction for power systems atte...
research
06/01/2022

Discrete-velocity-direction models of BGK-type with minimum entropy: I. Basic idea

In this series of works, we develop a discrete-velocity-direction model ...
research
11/15/2019

General Criteria for Successor Rules to Efficiently Generate Binary de Bruijn Sequences

We put forward new general criteria to design successor rules that gener...

Please sign up or login with your details

Forgot password? Click here to reset