Because experts may have uncertainty Fuzzy linguistic ranking model. Finally, in IFS are used to work with that uncertainty. Section V, the conclusions are presented. Multi Criteria Decision Making web. It is a tool used for problem accessible to everyone regardless of hardware, software, net- assessment and decision making with multiple alternatives that work infrastructure, language, culture, geographic location, or are evaluated considering multiple criteria [1], [2].
Currently there are several tools MCDM often deal with different types of problems such that evaluate the accessibility of websites automatically. The as selection, ranking and classification problems. The aim on tools contain different features that may or may not facilitate each kind of problem is different: 1 selection problems is the evaluation of the site depending on the context in which expected to find the best alternative; 2 the ranking problems are applied.
A DM is a typical problem which is presented as a hierarchy from the best to the worst that has different alternatives to choose from valued by experts and 3 in the classification problems we want to know which in the topic. Let wk be the usually people with experience in the subject to be assessed.
Alternatives can be assessed quantitatively or qualitatively. Boran et al. The separation of each alternative from the ideal is performed using the weight vector Wj and applying Eq. The ideal intuitionistic fuzzy positive as: and negative solutions are obtained as Eq. The final score of the alternatives performance is mity coefficient as: calculated by relative proximity as in Eq. Finally, the alternatives are ordered. The DM set three basic stages: 1 Representation phase, 2 Aggregation limits the main set to the six tools commonly used among phase and 3 Exploitation phase.
Figure 1 presents the them. It must be decided which of this set of six tools is best suited to your needs. The Fig. The linguistic intuitionistic variables in Set LTS that will be used for decision making.
In this step, the performance of each alternative should be calculated using the distance measurement from Fuzzy Criteria for evaluating accessibility assessment tools. The intuitionistic fuzzy ideal positive and c1 Learnability Enables simple and efficient learning. Allows evaluation on sites with user permissions from an negative solution are founded using Eq.
The c2 Scope of application external site. Describes the assessments: 1 failed, 2 warning and negative solution is calculated using the Eq. Evaluates accessibility of CSS content. Indicates inspected items for easy identification of errors, Finally, the alternatives are ordered by relative proximity as c8 Intuitivity warnings and approvals. Alternative a1 is selected as the best tool with the best scores in 6 of 9 criteria evaluated.
Also, scales enhances the assessment of alternatives in decision- using Table II , each DMk evaluates the performance of making problems because the cognitive processes of each alternative in each criterion. Table IV presents decision human beings accept words rather than numbers; makers assessments. Aggregation phase may be a degree of hesitation. IFS takes into account the Once the individual matrix of intuitionistic evaluations has degree of membership, degree of non-membership and been obtained, the matrix must be aggregated using the IFWA hesitancy; operator presented in Eq.
The IFWA information allows a better interpretability of results for operator is used to aggregate them into a group decision decision makers. Other access options You may be able to access this content by logging in via your Emerald profile.
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Abstract Purpose The purpose of the paper is to develop a model for the selection of knowledge management system KMS , in which the assessment criteria are defined and the TOPSIS method with multiple distances in fuzzy environment is proposed. Luukka, P. Collan, M. IEEE Trans. Fuzzy Syst. Turskis, Z. Wang, J. Hussi, T.
Alavi, M. MIS Q. Bao, Q. Based Syst. Kahraman, C. Paksoy, T. Hajek, P. Change 84 , — CrossRef Google Scholar. Matatkova, K. Transylvanian Rev. Petr Hajek 1 Email author Lucie Mansfeldova 2 1. Personalised recommendations. Cite paper How to cite? ENW EndNote.
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