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In this paper, we propose three outlier detection approaches for the fuzzy regression models proposed by Tanaka after a brief review of the related literatures. Generally speaking, for the upper regression model, the aim is to pick out some abnormal data that is not consistent with the trend of the upper regression model; for the lower regression model, as it often has no feasible solutions, the efforts...
This paper presents a quantitative decision making methodology for evaluating best alternative using benefits, opportunities, costs, and risks (BOCR) models together with the interval computation. The quantification using BOCR-interval arithmetic modeling is performed in association with two types of models: analytic network process (ANP) and analytic hierarchy process (AHP) via consensus of multiple...
This study applied relationship life cycle concept and separated two stages including relationship development and relationship maintenance to derivate influence factors in each stage based on relative literature for relationship development. This study proposed a model which called “Relationship Hierarchy Structural Fuzzy ANP Model”, and apply this model to investigate and compare interaction, influence,...
Purpose of this work is to develop norms, knowledge and algorithms that will make a real shift most of the educational process on the computer environment. On the basis of artificial neural networks, a mechanism, which allows taking into account, the subjective opinion of experts without requiring changes to the system. With the help of fuzzy logic developed an original method of monitoring the student's...
The importance of risk management for engineering, procurement and construction management (EPCM) projects has been progressively recognized over the last two decades. Researchers and practitioners alike introduced a wide range of methods to analyze and evaluate risks. Several methods were developed using fuzzy set theory in view of its capabilities for modeling projects risk quantitatively and qualitatively,...
A key requirement for using a simulation model to assess a highly complex system is the ability to characterize and quantify the uncertainty in the simulation results with respect to a typically immense set of possible combinations of values of the model's input parameters. Some of these inputs may be sampled from a known or assumed probability distribution, but others are known only possibilistically...
The advantages of intelligent methods and fuzzy models for the analysis and linguistic interpretation of non-linear dependences in source data are used in Internet service for the express analysis of enterprise economic indicators time series.
This paper presents results of research into the use of models and methods of multicriteria decision making in a fuzzy environment for solving power engineering problems. Two classes of models associated with multiobjective (<X, M> models) and multiattribute (<X, R> models) problems, as well as methods for their analysis are briefly discussed. A review of the authors' results related to...
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