The wireless industry is rapidly transitioning from proprietary architecture to more flexible, cost effective open wireless architecture (OWA) systems. This transition is creating interesting challenges for developers, manufacturers, integrators, operators and end-users as they wrestle with complexities of open wireless systems. Fourth Generation (4G) Mobile Communications should not focus only...

In this paper, we first review existing fuzzy extensions of the dominance-based rough set approach (DRSA), and advance theory considering additional properties. Moreover, examine application Ordered Weighted Average (OWA) operators to DRSA. OWA have shown a lot potential in handling outliers noisy data decision tables, when they are combined with indiscernibility-based (IRSA). We theoretical pr...

Social media are an essential source of meaningful data that can be used in different tasks such as sentiment analysis and emotion recognition. Mostly, these solved with deep learning methods. Due to the fuzzy nature textual data, we consider using classification methods based on rough sets.Specifically, develop approach for SemEval-2018 detection task, nearest neighbour (FRNN) classifier enhan...

این پژوهش با الهام گرفتن از نتایج یک طرح مطالعاتی کاربردی، رویکرد سلسله­‌مراتبی جهت پیگیری فرایند توسعه تأمین‌کنندگان و حمایت تصمیمات موجود در هر مراحل آن ارائه‌ می‌کند. ابتدا، زمینه‌های تأمین نیازمند سپس واجد شرایط هریک زمینه‌ها به کمک تصمیم‌گیری چندشاخصه بهترین-بدترین مشخص می‌گردند. معیارهای شناسایی نیز مرور مطالعات پیشین بهره‌گیری نظرات خبرگان حوزه‌ی خرید استخراج‌شده‌اند. درنهایت، مدل ریاضی ...

The OWA operators gained interest among researchers as they provide a continuum of aggregation operators able to cover the whole range of compensation between the minimum and the maximum. In some circumstances, it is useful to consider a wider range of values, extending below the minimum and over the maximum. ST-OWA are able to surpass the boundaries of variation of ordinary compensatory operat...

We introduce a new aggregation operator called the heavy ordered weighted averaging – weighted averaging (HOWAWA) operator. It is a new aggregation operator that uses the weighted average and the ordered weighted average in the same formulation and considering the degree of importance that each concept has in the analysis. Moreover, by using heavy aggregations, we are allowing the weighting vec...

We develop a new model for decision making under risk environment and under uncertainty. We introduce a new aggregation operator that unifies the probabilities and the ordered weighted averaging (OWA) operator in the same formulation. We call it the probabilistic ordered weighted averaging (POWA) operator. This aggregation operator provides a more complete representation of the decision problem...