clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

since the pioneering work of zadeh, fuzzy set theory has been applied to amyriad of areas. song and chissom introduced the concept of fuzzy time series andapplied some methods to the enrolments of the university of alabama. thereafter weapply fuzzy techniques for system identification and apply statistical techniques tomodelling system. an automatic methodology framework that combines fuzzytech...

in this work, the time series modeling was used to predict the tazareh coal mine risks. for this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. next, a monthly time series diagram related to each one of these indices was for a nine year period of time from 2005 to 2013. after extrusion of the trend, seasonali...

despite recent advances in video inpainting techniques, reconstructing large missing regions of a moving subject while its scale changes remains an elusive goal. in this paper, we have introduced a scale-change invariant method for large missing regions to tackle this problem. using this framework, first the moving foreground is separated from the background and its scale is equalized. then, a ...

abstract prediction of input flow into water resources is regarded as one of the most important issues in optimum planning and management in producing electro-water energy and optimum allocation of water into different consumption sources. different parameters affect on input discharge into dams. climate variables including temperature and rainfall have the most effect on input runoff rate to w...