Discussion on Normalization Methods of Interval Weights

نویسندگان

  • Yimeng Sui
  • Zhenyuan Wang
چکیده

This paper is collecting the classic and newly normalization methods, finding deficiency of existing normalization methods for interval weights, and introducing a new normalization methods for interval weights. When we normalize the interval weights, it is very important and necessary to check whether, after normalizing, the location of interval centers as well as the length of interval weights keep the same proportion as those of original interval weights. It is found that, in some newly normalization methods, they violate these goodness criteria. In current work, for interval weights, we propose a new normalization method that reserves both proportions of the distances from interval centers to the origin and of interval lengths, and also eliminates the redundancy from the original given interval weights. This new method can be widely applied in information fusion and decision making in environments with uncertainty.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Interval estimations of global weights in AHP by upper approximation

In Analytic Hierarchy Process (AHP) structured hierarchically as several criteria and alternatives, the priority of an alternative is obtained by using the pairwise comparisons based on decision maker’s intuition. Thus, the given comparisons are uncertain and inconsistent each other. We use the interval approach for obtaining interval evaluations which are suitable for handling uncertain data. ...

متن کامل

L2 Regularization versus Batch and Weight Normalization

Batch Normalization is a commonly used trick to improve the training of deep neural networks. These neural networks use L2 regularization, also called weight decay, ostensibly to prevent overfitting. However, we show that L2 regularization has no regularizing effect when combined with normalization. Instead, regularization has an influence on the scale of weights, and thereby on the effective l...

متن کامل

Interval-Valued Hesitant Fuzzy Method based on Group Decision Analysis for Estimating Weights of Decision Makers

In this paper, a new soft computing group decision method based on the concept of compromise ratio is introduced for determining decision makers (DMs)' weights through the group decision process under uncertainty. In this method, preferences and judgments of the DMs or experts are expressed by linguistic terms for rating the industrial alternatives among selected criteria as well as the relativ...

متن کامل

Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection

A target-based MADM method covers beneficial and non-beneficial attributes besides target values for some attributes. Such techniques are considered as the comprehensive forms of MADM approaches. Target-based MADM methods can also be used in traditional decision-making problems in which beneficial and non-beneficial attributes only exist. In many practical selection problems, some attributes ha...

متن کامل

Normalization of qPCR array data: a novel method based on procrustes superimposition

MicroRNAs (miRNAs) are short, endogenous non-coding RNAs that function as guide molecules to regulate transcription of their target messenger RNAs. Several methods including low-density qPCR arrays are being increasingly used to profile the expression of these molecules in a variety of different biological conditions. Reliable analysis of expression profiles demands removal of technical variati...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016