Description and classification of granular time series

Rami Al-Hmouz*, Witold Pedrycz, Abdullah Balamash, Ali Morfeq

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

14 اقتباسات (Scopus)


The study is concerned with a concept and a design of granular time series and granular classifiers. In contrast to the plethora of various models of time series, which are predominantly numeric, we propose to effectively exploit the idea of information granules in the description and classification of time series. The numeric (optimization-oriented) and interpretation abilities of granular time series and their classifiers are highlighted and quantified. A general topology of the granular classifier involving a formation of a granular feature space and the usage of the framework of relational structures (relational equations) in the realization of the classifiers is presented. A detailed design process is elaborated on along with a discussion of the pertinent optimization mechanisms. A series of experiments is covered leading to a quantitative assessment of the granular classifiers and their parametric analysis.

اللغة الأصليةEnglish
الصفحات (من إلى)1003-1017
عدد الصفحات15
دوريةSoft Computing
مستوى الصوت19
رقم الإصدار4
المعرِّفات الرقمية للأشياء
حالة النشرPublished - أبريل 2015

ASJC Scopus subject areas

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