Software is everywhere. However, software is not always trustworthy. Confronting the demand of software trustworthiness evaluation, this paper proposes a novel software trustworthiness evaluation approach based on combination weights (CW) and improved TOPSIS methods. The determination of CW relies on exper gments and mathematical computation together. FAHP method is used to determine the import...

Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

The main task of this paper is to develop a new decision making method based on a novel entropy measure of intuitionistic fuzzy sets. First a novel intuitionistic fuzzy entropy is constructed, then based on this information measure, new weighting methods are proposed for the intuitionistic fuzzy decision making problems with the attribute weights are completely unknown or partly known. Further ...

Application of Group Decision Support System (GDSS) can assist for delivering the decision of various opinions (preference) cancer detection based on the preferences of various expertise. In this paper we propose ELECTRE-Entropy for GDSS Modeling. We propose entropy weighting for each criteria under ELECTRE Method.ELECTRE is one method in MultiAttribute Decision Making (MADM). Modeling of Group...

predicting different behaviors in computer networks is the subject of many data mining researches. providing a balanced intrusion detection system (ids) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

Supervised term weighting could improve the performance of text categorization. A way proven to be effective is to give more weight to terms with more imbalanced distributions across categories. This paper shows that supervised term weighting should not just assign large weights to imbalanced terms, but should also control the trade-off between over-weighting and under-weighting. Overweighting,...

First we modify the basic (binary) context-tree weighting method such that the past symbols x1 D; x2 D; ; x0 are not needed by the encoder and the decoder. Then we describe how to make the context-tree depth D infinite, which results in optimal redundancy behavior for all tree sources, while the number of records in the context tree is not larger than 2T 1: Here T is the length of the source se...

First we modify the basic (binary) context-tree weighting method such that the past symbols x1 D; x2 D; ; x0 are not needed by the encoder and the decoder. Then we describe how to make the context-tree depth D infinite, which results in optimal redundancy behavior for all tree sources, while the number of records in the context tree is not larger than 2T 1: Here T is the length of the source se...

An adaptive and parameter-free image fusion method for multiple exposures of a static scene captured by a stationary camera is described. The notion of a statistical convolution operator is discussed and convolution by entropy is introduced. Images are fused by weighting pixels with the amount of information present in their local surroundings. The proposed fusion approach is solely based on no...