{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:44:52Z","timestamp":1777704292152,"version":"3.51.4"},"reference-count":24,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,4,12]]},"abstract":"<jats:p>In today\u2019s society, graphic design, as a popular image processing technology, plays an increasingly important role in people\u2019s lives. In the specific operation process of graphic design, It is no longer restricted to the traditional development mode, such as file format and other factors. With the development of computer network technology, people promote the development of graphic design by constructing color management system. At the same time, the construction of color management system can help people to change colors and define colors when they process image information and output pictures. In the process of printing pictures, in order to make the colors used in the design process clearly printed out and without color difference, there are still many problems to be considered. First, we need to consider the unexpected situation and the complexity of image processing. Based on the introduction of computer learning, this paper will discuss and study the development of graphic design by SVM theory.<\/jats:p>","DOI":"10.3233\/jifs-189515","type":"journal-article","created":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T10:13:32Z","timestamp":1608286412000},"page":"6827-6838","source":"Crossref","is-referenced-by-count":4,"title":["Color image design based on machine learning and SVM algorithm"],"prefix":"10.1177","volume":"40","author":[{"given":"Li","family":"Bo","sequence":"first","affiliation":[{"name":"Shool of Communication Engineering, Shenzhen Polytechnic, Shenzhen, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"9","key":"10.3233\/JIFS-189515_ref1","doi-asserted-by":"crossref","first-page":"1413","DOI":"10.1016\/j.energy.2009.06.034","article-title":"Electricity consumption forecasting in Italy using linear regression models","volume":"34","author":"Bianco","year":"2009","journal-title":"Energy"},{"issue":"1","key":"10.3233\/JIFS-189515_ref2","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.ijar.2019.05.002","article-title":"Designing fuzzy time series forecasting models: a survey","volume":"11","author":"Bose","year":"2019","journal-title":"Int J Approximate Reasoning"},{"issue":"9","key":"10.3233\/JIFS-189515_ref3","first-page":"300","article-title":"Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology","volume":"18","author":"Botchkarev","year":"2018","journal-title":"arXiv preprint arXiv"},{"issue":"6","key":"10.3233\/JIFS-189515_ref4","first-page":"161","article-title":"Box and Jenkins: time series analysis, forecasting and control. 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