A. Chattopadhyay, M. H. Khondekar, A. Bhattacharjee
{"title":"CME线性速度时间序列的复杂度","authors":"A. Chattopadhyay, M. H. Khondekar, A. Bhattacharjee","doi":"10.1109/ICSPCOM.2016.7980627","DOIUrl":null,"url":null,"abstract":"In this article, an effort has been made to investigate the nonlinear and chaotic nature of daily CME linear speed time series data collected from the Solar and Heliospheric Observatory for solar cycle 23 over the period of February 1999 to December 2007. To explore the nonlinear characteristic of the CME linear speed signal delay vector variance algorithm is used whereas 0–1 test, information entropy and also correlation dimension methods are performed to investigate the chaotic behaviour of the signal. The result of these analyses suggests that the CME linear speed time series signal generated source is definitely nonlinear and deterministic with chaotic behaviour which validates that the possibilities of forecasting for long duration is nearly impossible but forecasting for short span can be achieved on condition that the underlying dynamics of the process must be known.","PeriodicalId":213713,"journal":{"name":"2016 International Conference on Signal Processing and Communication (ICSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Complexity of CME linear speed time series\",\"authors\":\"A. Chattopadhyay, M. H. Khondekar, A. Bhattacharjee\",\"doi\":\"10.1109/ICSPCOM.2016.7980627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, an effort has been made to investigate the nonlinear and chaotic nature of daily CME linear speed time series data collected from the Solar and Heliospheric Observatory for solar cycle 23 over the period of February 1999 to December 2007. To explore the nonlinear characteristic of the CME linear speed signal delay vector variance algorithm is used whereas 0–1 test, information entropy and also correlation dimension methods are performed to investigate the chaotic behaviour of the signal. The result of these analyses suggests that the CME linear speed time series signal generated source is definitely nonlinear and deterministic with chaotic behaviour which validates that the possibilities of forecasting for long duration is nearly impossible but forecasting for short span can be achieved on condition that the underlying dynamics of the process must be known.\",\"PeriodicalId\":213713,\"journal\":{\"name\":\"2016 International Conference on Signal Processing and Communication (ICSC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Signal Processing and Communication (ICSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCOM.2016.7980627\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Signal Processing and Communication (ICSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCOM.2016.7980627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this article, an effort has been made to investigate the nonlinear and chaotic nature of daily CME linear speed time series data collected from the Solar and Heliospheric Observatory for solar cycle 23 over the period of February 1999 to December 2007. To explore the nonlinear characteristic of the CME linear speed signal delay vector variance algorithm is used whereas 0–1 test, information entropy and also correlation dimension methods are performed to investigate the chaotic behaviour of the signal. The result of these analyses suggests that the CME linear speed time series signal generated source is definitely nonlinear and deterministic with chaotic behaviour which validates that the possibilities of forecasting for long duration is nearly impossible but forecasting for short span can be achieved on condition that the underlying dynamics of the process must be known.