Based on multi-attribute decision making theory, a multi-attribute assessment framework for Ecommerce risks is presented. The paper applies an improved evidential reasoning(ER) approach to support evaluation decision, and uses a credit interval to figure scoring result and allow something absence. E-Commerce risks includes environmental risks, management risks, technical risks and information r...

Because of the complexity of limitation and realistic decision of decision knowledge, multiple attribute decision making problems with the attribute value often need to characterize fuzzy number. The triangular fuzzy number to describe this kind of ambiguity is very effective and for the project investment selection problem with triangular fuzzy numbers, this study puts forward a new multiple a...

With respect to multiple attribute decision making problems with linguistic information of attribute values and weight values, a decision analysis is proposed. Then, a method based on the ET-WA operator for multiple attribute decision making is presented. In the approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alter...

To characterize the influence of decision makers’ psychological factors on the group decision process, this paper develops a new class of aggregation operators based on reference-dependent utility functions (RUs) in multi-attribute group decision analysis. We consider two types of RUs: S-shaped, representing decision makers who are risk-seeking for relative losses, and non-S-shaped, representin...

This paper presents a Multi-Attribute Decision Support System aimed at aiding decision-makers in identifying optimal alternatives in complex decision-making problems. The system is based on a multi-attribute additive value model and admits imprecise assignments concerning weights and utilities and uncertainty about the multi-attribute alternatives. Different sensitivity analyses are possible ov...

36 www.ijeas.org  Abstract—The genetic algorithm is used to optimize the algorithm of attribute reduction in data preprocessing, and the rough approximation precision in the rough set theory is utilized to determine the importance of information attribute. From which the decision table is constituted by selecting the attributes which have higher degree of attribute importance, and the attribut...

In KDD procedure, to fill in missing data typically requires a very large investment of time and energy often 80% to 90% of a data analysis project is spent in making the data reliable enough so that the results can be trustful. In this paper, we propose a SVM regression based algorithm for filling in missing data, i.e. set the decision attribute (output attribute) as the condition attribute (i...

The fundamental problem underlying all multi-criteria decision analysis (MCDA) problems is that of dominance between any two alternatives: ‘Given two alternatives A and B, each described by a set criteria, is A preferred to B with respect to a set of decision maker (DM) preferences over the criteria?’. Depending on the application in which MCDA is performed, the alternatives may represent strat...

The purpose of this paper is to extend a new balancing and ranking method to handle uncertainty for a multiple attribute analysis under a hesitant fuzzy environment. The presented hesitant fuzzy balancing and ranking (HF-BR) method does not require attributes’ weights through the process of multiple attribute decision making (MADM) under hesitant conditions. For the rating of possible alternati...

The aim of this paper is to investigate the multiple attribute decision making problems to deal with supplier selection with intuitionistic trapezoidal fuzzy information, in which the information about attribute weights is completely known, and the attribute values take the form of intuitionistic trapezoidal fuzzy number. We developed a multiple attribute decision making method by closeness to ...