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The screening of new product ideas is critically very important in new product development (NPD). Due to the incompleteness of information available and the qualitative nature of most evaluation criteria regarding NPD process, a fuzzy linguistic approach may be necessary for new-product screening, making use of linguistic assessments and the fuzzy-set-based computation. However, an inherent limitation...
As a branch of Group Decision-Making Method, Grade division plays an important role in many applications such as hazard assessment, quality evaluation, and performance inspection and so on. At present, the most popular grade division method is fuzzy comprehensive evaluation, which determines the decision objects' grade through analysis of evaluation vector. One problem with this approach is that it...
One of the most important phases in business-to-business-based electronic construction bid is the process of bidding decision-making module whose operating optimization is considered to be the foundation of implementing the integration of B2B-based bid mode. Strategies facilitating the optimization of E-bidding are demonstrated in this paper: in order to utilize the efficiency and effectiveness both...
This article has used data mining techniques and fuzzy comprehensive evaluation model to analyze and deal with a large number of complex data and information of programme management (PgM), and founds that valuable knowledge. When analyzing and making programme selection, the author establishes the fuzzy comprehensive evaluation model and AHP(the analytic hierarchy process), calculates on comparative...
A classical model for substantiating decisions has as input data the matrix of the results obtained for each criterion and each decision variant. Often, the values of the results are uncertain because they are expressed by statements such as "the value is around b, certainly it is not less than a and does not exceeds c", (alesblesc), which is mathematically modelled by triangular fuzzy numbers...
Due to the learning problem on skewed distribution datasets, which tend to produce high accuracy over the majority class but poor predictive accuracy over the minority class by traditional machine learning algorithms, fuzzy information granulation based knowledge discovery and decision support model called FIG mode is proposed in this paper to improve classification performance and make effective...
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