the present paper aimed at developing an approach based on fuzzy inference system (fis) for measuring of knowledge sharing in the organization. in recent years there has been increasing interest in the knowledge sharing by experts and managers in the world, according to increasing importance of knowledge as the key source of competitive advantage, organizations have made serious effort to find ...

Many studies on modeling of fuzzy inference systems have been made. The issue of these studies is to construct automatically fuzzy inference systems with interpretability and accuracy from learning data based on metaheuristic methods. Since accuracy and interpretability are contradicting issues, there are some disadvantages for self-tuning method by metaheuristic methods. Obvious drawbacks of t...

An increasing number of applications require the integration of data from various disciplines, which leads to problems with the fusion of multi-source information. In this paper, a special information structure formalized in terms of three indices (the central presentation, population or scale, and density function) is proposed. Single and mixed Gaussian models are used for single source inform...

Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

In this paper a fuzzy model based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is introduced for calculating the level of risk in managerial problems. In this model, affecting factors on the level of risk are considered as inputs and the level of risk as the output. Using the fuzzy model, the risky condition changes smoothly in a fuzzy environment as it is the case in the real world; while ...

some applications are critical and must designed fault tolerant system. usually voting algorithm is one of the principle elements of a fault tolerant system. two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. majority confronts with the problem of threshold limits and voter of weight...

This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is propo...

To improve the problem that the parameter identification for fuzzy neural network has many time complexities in calculating, an improved T-S fuzzy inference method and an parameter identification method for fuzzy neural network are proposed. It mainly includes three parts. First, improved fuzzy inference method based on production term for T-S Fuzzy model is explained. Then, compared with exist...

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...