Biblio

Smart Grid cyber-security sounds to be a critical issue, because of widespread development of information technology. To achieve secure and reliable operation, the complexity of human automation interaction (HAI) necessitates more sophisticated and intelligent methodologies. In this paper, an adaptive autonomy fuzzy expert system is developed using gradient descent algorithm to determine the Level of Automation (LOA), based on the changing of Performance Shaping Factors (PSF). These PSFs indicate the effects of environmental conditions on the performance of HAI. The major advantage of this method is that the fuzzy rule or membership function can be learnt without changing the form of the fuzzy rule in conventional fuzzy control. Because of data shortage, Leave-One-Out Cross-Validation (LOOCV) technique is applied for assessing how the results of proposed system generalizes to the new contingency situations. The expert system database is extracted from superior experts' judgments. In order to regard the importance of each PSF, weighted rules are also considered. In addition, some new environmental conditions are introduced that has not been seen before. Nine scenarios are discussed to reveal the performance of the proposed system. Results confirm that the presented fuzzy expert system can effectively calculates the proper LOA even in the new contingency situations.

A variety of methods for images noise reduction has been developed so far. Most of them successfully remove noise but their edge preserving capabilities are weak. Therefore bilateral image filter is helpful to deal with this problem. Nevertheless, their performances depend on spatial and photometric parameters which are chosen by user. Conventionally, the geometric weight is calculated by means of distance of neighboring pixels and the photometric weight is calculated by means of color components of neighboring pixels. The range of weights is between zero and one. In this paper, geometric weights are estimated by fuzzy metrics and photometric weights are estimated by using fuzzy rule based system which does not require any predefined parameter. Experimental results of conventional, fuzzy bilateral filter and proposed approach have been included.