The portfolio construction problem usually has been viewed in the framework of risk-return trade-off. Using deterministic and stochastic portfolio models used to solve the problem lead to unrealistic results as both the expected return rate and the risk are vague. Moreover, the decision maker frequently deals with insufficient data when selecting a portfolio. Using fuzzy models allows removal o...

Fuzzy logic has proved in this paper, a medical fuzzy data is introduced in order to help users in providing accurate information when there is inaccuracy. Inaccuracy in data represents imprecise or vague values (like the words use in human conversation) or uncertainty in using the available information required for decision making handle the uncertainty of critical risk for human health. In th...

one of the most important strategies for governments to increase the efficiency of different economic sectors, including public services such as water, is to protect and strengthen the private sector. bot and boo contracts are among the most common and popular procedures of development of participation and investment from private sector. in this context, providing a good basis for the selection...

|To design a fuzzy rule-based classi cation system (fuzzy classi er) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high (or e...

this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

The backing of the fuzzy ideal is normal ideal in some ring and in same time there fuzzy set whose is not fuzzy ideal and it backing set is ideal, i.e., it crisp is normal ideal. Consequently, in this paper we constructing a fuzziness function which defined on fuzzy sets and assigns membership grade for every fuzzy set whose it backing set are crisp ideal. Now, Let  be collection of all fuzzy s...

Fuzzy risk analysis, as a powerful tool to address uncertain information, can provide an appropriate method for risk analysis. However, the previous fuzzy risk analysis methods still have some weaknesses. To overcome the weaknesses of existing fuzzy risk analysis methods, a novel method for ranking generalized fuzzy numbers is proposed for addressing fuzzy risk analysis problems. In the propose...

Cost-sensitive classification is based on a set of weights defining the expected cost of misclassifying an object. In this paper, a Genetic Fuzzy Classifier, which is able to extract fuzzy rules from interval or fuzzy valued data, is extended to this type of classification. This extension consists in enclosing the estimation of the expected misclassification risk of a classifier, when assessed ...