An Intelligent Gray Prediction Model Based on Fuzzy Theory

In order to improve the forecasting effect of the gray prediction model, this paper combines the fuzzy theory to construct the gray prediction model and explores its forecasting accuracy. Moreover, this paper uses the entropy weight method to obtain the objective weight to correct the subjective wei...

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Main Author: Weili Wu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:International Transactions on Electrical Energy Systems
Online Access:http://dx.doi.org/10.1155/2022/8618586
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author Weili Wu
author_facet Weili Wu
author_sort Weili Wu
collection DOAJ
description In order to improve the forecasting effect of the gray prediction model, this paper combines the fuzzy theory to construct the gray prediction model and explores its forecasting accuracy. Moreover, this paper uses the entropy weight method to obtain the objective weight to correct the subjective weight, which makes the weight calculation more reasonable. In view of the uncertainty of the control signal of the research object, this paper introduces the gray system theory to conduct cluster analysis on the fire control computer and mainly introduces the general whitening weight function. Furthermore, this paper adopts the center point mixed with a triangular whitening weight function to carry out gray clustering according to the difficulty of defining the gray class boundary and gives the solution steps to obtain the intelligent gray prediction model. Finally, this paper verifies that the intelligent gray prediction model based on fuzzy theory has a good effect through experiments, which can effectively improve the prediction effect of the intelligent prediction model.
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institution Kabale University
issn 2050-7038
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series International Transactions on Electrical Energy Systems
spelling doaj-art-d0474daa21774d59b48ab03355b864422025-02-03T01:23:37ZengWileyInternational Transactions on Electrical Energy Systems2050-70382022-01-01202210.1155/2022/8618586An Intelligent Gray Prediction Model Based on Fuzzy TheoryWeili Wu0School of Mathematics and StatisticsIn order to improve the forecasting effect of the gray prediction model, this paper combines the fuzzy theory to construct the gray prediction model and explores its forecasting accuracy. Moreover, this paper uses the entropy weight method to obtain the objective weight to correct the subjective weight, which makes the weight calculation more reasonable. In view of the uncertainty of the control signal of the research object, this paper introduces the gray system theory to conduct cluster analysis on the fire control computer and mainly introduces the general whitening weight function. Furthermore, this paper adopts the center point mixed with a triangular whitening weight function to carry out gray clustering according to the difficulty of defining the gray class boundary and gives the solution steps to obtain the intelligent gray prediction model. Finally, this paper verifies that the intelligent gray prediction model based on fuzzy theory has a good effect through experiments, which can effectively improve the prediction effect of the intelligent prediction model.http://dx.doi.org/10.1155/2022/8618586
spellingShingle Weili Wu
An Intelligent Gray Prediction Model Based on Fuzzy Theory
International Transactions on Electrical Energy Systems
title An Intelligent Gray Prediction Model Based on Fuzzy Theory
title_full An Intelligent Gray Prediction Model Based on Fuzzy Theory
title_fullStr An Intelligent Gray Prediction Model Based on Fuzzy Theory
title_full_unstemmed An Intelligent Gray Prediction Model Based on Fuzzy Theory
title_short An Intelligent Gray Prediction Model Based on Fuzzy Theory
title_sort intelligent gray prediction model based on fuzzy theory
url http://dx.doi.org/10.1155/2022/8618586
work_keys_str_mv AT weiliwu anintelligentgraypredictionmodelbasedonfuzzytheory
AT weiliwu intelligentgraypredictionmodelbasedonfuzzytheory