{"title":"模糊集理论在区域创新发展指标计算中的应用——以俄罗斯亚马尔地区为例","authors":"S. Gutman, A. Kozlov, E. Rytova, I. Zaychenko","doi":"10.1109/SCM.2015.7190486","DOIUrl":null,"url":null,"abstract":"The goal of the research was the calculating of the aggregated indicator of innovation development level in a region based on the fuzzy logic theory. Applying the fuzzy logic approach for aggregate indicator's estimating allows to take experts assessments into account which is especially important when the statistic data is insufficient or lean. As the result there were defined factors affecting the innovation development level of a region, there was defined a linguistic scale for the aggregated indicator, the indicator was calculated for the Yamal region of Russia. The method could be applied to monitoring of innovation development of the Russian regions.","PeriodicalId":106868,"journal":{"name":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"The application of the fuzzy set theory to counting a regional innovative development indicators: The case of the Yamal region of the Russian Federation\",\"authors\":\"S. Gutman, A. Kozlov, E. Rytova, I. Zaychenko\",\"doi\":\"10.1109/SCM.2015.7190486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of the research was the calculating of the aggregated indicator of innovation development level in a region based on the fuzzy logic theory. Applying the fuzzy logic approach for aggregate indicator's estimating allows to take experts assessments into account which is especially important when the statistic data is insufficient or lean. As the result there were defined factors affecting the innovation development level of a region, there was defined a linguistic scale for the aggregated indicator, the indicator was calculated for the Yamal region of Russia. The method could be applied to monitoring of innovation development of the Russian regions.\",\"PeriodicalId\":106868,\"journal\":{\"name\":\"2015 XVIII International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 XVIII International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCM.2015.7190486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCM.2015.7190486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of the fuzzy set theory to counting a regional innovative development indicators: The case of the Yamal region of the Russian Federation
The goal of the research was the calculating of the aggregated indicator of innovation development level in a region based on the fuzzy logic theory. Applying the fuzzy logic approach for aggregate indicator's estimating allows to take experts assessments into account which is especially important when the statistic data is insufficient or lean. As the result there were defined factors affecting the innovation development level of a region, there was defined a linguistic scale for the aggregated indicator, the indicator was calculated for the Yamal region of Russia. The method could be applied to monitoring of innovation development of the Russian regions.
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