{"title":"Optimal Alpha Level Setting in GM (1, 1) Model Based on Genetic Algorithm","authors":"Kuo-Chen Hung, Chia-Yi Chien, Kuo-Jung Wu, Fu-Yuan Hsu","doi":"10.30016/JGS.200903.0004","DOIUrl":null,"url":null,"abstract":"The grey forecasting model, GM (1, 1), with the property of processing with a minimum of data, has been successfully applied in various fields. However, it has been discovered that different errors may be directly induced by different alpha levels in predicted operations. Accordingly, the parameter α plays an important role on forecasting. Thus, how to search for the optimal setting of parameter α is a valuable work. In this paper, Genetic Algorithm (GA) method has be applied in GM (1, 1) model for handling this problem. We present two illustrative examples to compare between Deng's method and our revised method. These results are useful in that they diminish the margin of error.","PeriodicalId":50187,"journal":{"name":"Journal of Grey System","volume":"12 1","pages":"23-31"},"PeriodicalIF":1.0000,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Grey System","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.30016/JGS.200903.0004","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 18
Abstract
The grey forecasting model, GM (1, 1), with the property of processing with a minimum of data, has been successfully applied in various fields. However, it has been discovered that different errors may be directly induced by different alpha levels in predicted operations. Accordingly, the parameter α plays an important role on forecasting. Thus, how to search for the optimal setting of parameter α is a valuable work. In this paper, Genetic Algorithm (GA) method has be applied in GM (1, 1) model for handling this problem. We present two illustrative examples to compare between Deng's method and our revised method. These results are useful in that they diminish the margin of error.
期刊介绍:
The journal is a forum of the highest professional quality for both scientists and practitioners to exchange ideas and publish new discoveries on a vast array of topics and issues in grey system. It aims to bring forth anything from either innovative to known theories or practical applications in grey system. It provides everyone opportunities to present, criticize, and discuss their findings and ideas with others. A number of areas of particular interest (but not limited) are listed as follows:
Grey mathematics-
Generator of Grey Sequences-
Grey Incidence Analysis Models-
Grey Clustering Evaluation Models-
Grey Prediction Models-
Grey Decision Making Models-
Grey Programming Models-
Grey Input and Output Models-
Grey Control-
Grey Game-
Practical Applications.