25 آبان 1403
سعيد طهماسبي

سعید طهماسبی

مرتبه علمی: دانشیار
نشانی: دانشکده مهندسی سیستم های هوشمند و علوم داده - گروه آمار
تحصیلات: دکترای تخصصی / آمار ریاضی
تلفن: 077-31223329
دانشکده: دانشکده مهندسی سیستم های هوشمند و علوم داده

مشخصات پژوهش

عنوان Measures of extended fractional Deng entropy and extropy with applications
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Classification and discrimination; Decomposable fractional Deng entropy Deng entropy and extropy; Fractional entropy; Measures of uncertainty
مجله COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
شناسه DOI 10.1080/03610918.2024.2391877
پژوهشگران نسترن مرزبان واصل آبادی (نفر اول) ، سعید طهماسبی (نفر دوم) ، احمد کشاورز (نفر سوم) ، Francesco Buono (نفر چهارم)

چکیده

Recently, Zhang and Shang introduced modifications to the concept of fractional entropy and proved some properties based on the inverse Mittag-Leffler function (MLF). The Deng entropy serves as a valuable measure in the Dempster-Shafer evidence theory (DST) to tackle uncertainty. In this study, we extend the fractional Deng entropy measure, introducing two distinct versions:We call this new measure the extended fractional Deng entropy, EFDEn. Additionally, we apply a similar approach to the fractional Deng extropy measure, We call this new measure the extended fractional Deng extropy, EFDEx. These two measures are complementary, leading to provide a deeper analysis of known and unknown information. Subsequently, we conduct a comparative analysis of these measures within the DST framework. We also propose the decomposable fractional Deng entropy, an extension of the decomposable entropy for Dempster–Shafer evidence theory, which effectively decomposes fractional Deng entropy. Finally, we delve into a pattern recognition classification problem to highlight the importance of these new measures.