Generalized Aggregate Uncertainty Measure 2 for Uncertainty Evaluation of a Dezert-Smarandache Theory based Localization Problem
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
In this paper, Generalized Aggregated Uncertainty measure 2 (GAU2), as a new uncertainty measure, is considered to evaluate uncertainty in a localization problem in which cameras images are used. The theory that is applied to a hierarchical structure for a decision making to combine cameras images is Dezert-Smarandache theory. To evaluate decisions, an analysis of uncertainty is executed at every level of the decision-making system. The second generalization of Aggregated Uncertainty measure (GAU2) which is applicable for DSmT results is used as a supervisor. The GAU2 measure in spite of the GAU1 measure can be applied to the problems with vague borders or continuous events. This measure may help to make decisions based on better preference combinations of sensors or methods of fusion. GAU2 is used to evaluate uncertainty after applying classic DSmT and hybrid DSmT with extra knowledge. Therefore by using the decision making system, results with less uncertainty are generated in spite of high conflict sensory data.
Keywords:
Language:
English
Published:
Journal of Modeling and Simulation, Volume:49 Issue: 2, Autumn 2017
Pages:
153 to 162
magiran.com/p1794781
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یکساله به مبلغ 1,390,000ريال میتوانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
- حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران میشود.
- پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانههای چاپی و دیجیتال را به کاربر نمیدهد.
In order to view content subscription is required
Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!