{"title":"Trend detection based on a fuzzy temporal profile model","authors":"P. Félix , S. Fraga , R. Marı́n , S. Barro","doi":"10.1016/S0954-1810(99)00006-0","DOIUrl":null,"url":null,"abstract":"<div><p>A fuzzy temporal profile (FTP) is a model through which we describe the evolution of a certain physical parameter <em>V</em> over time. Thus we define a set of significant points (<em>X</em><sub>0</sub>,<em>X</em><sub>1</sub>,…,<em>X</em><sub><em>N</em></sub>), and we approximate the evolution curve by way of linear sections between them. Each section is defined by way of an imprecise constraint on duration, on increase in value and on slope between the points connected by the section.</p><p>In this article we show a possible method of matching an FTP with a signal, which will enable the detection of profiles of interest on the trace of a physical parameter over time.</p></div>","PeriodicalId":100123,"journal":{"name":"Artificial Intelligence in Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1999-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0954-1810(99)00006-0","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0954181099000060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
A fuzzy temporal profile (FTP) is a model through which we describe the evolution of a certain physical parameter V over time. Thus we define a set of significant points (X0,X1,…,XN), and we approximate the evolution curve by way of linear sections between them. Each section is defined by way of an imprecise constraint on duration, on increase in value and on slope between the points connected by the section.
In this article we show a possible method of matching an FTP with a signal, which will enable the detection of profiles of interest on the trace of a physical parameter over time.