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We introduce some notions, such as picture fuzzy ideal point, the normalized Hamming distance of picture fuzzy numbers. We also introduce the grey relational coefficient between the attribute value vectors of each alternative and the picture fuzzy ideal point. Then we establish the grey relational analysis models to measure the grey relational degree between each alternative and the picture fuzzy ideal point. Based on the grey relational analysis models, we can rank the given alternatives and then select the most desirable one. Finally, we illustrate the developed grey relational analysis models with a numerical example for potential evaluation of emerging technology commercialization.<\/jats:p>","DOI":"10.3233\/jifs-179259","type":"journal-article","created":{"date-parts":[[2019,6,25]],"date-time":"2019-06-25T12:38:27Z","timestamp":1561466307000},"page":"1973-1980","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["Models for multiple attribute decision making with picture fuzzy information"],"prefix":"10.1177","volume":"37","author":[{"given":"Hui","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, Shangdong, China"},{"name":"Medical Physics Division in the Department of Radiation Oncology, Stanford University, Palo Alto, CA, USA"},{"name":"Digital Media Technology Key Lab of Shandong Province, Jinan, Shandong, 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