in recent years, interest in climatic extreme events (droughts, floods and heat waves) has been growing not only due to their direct impact on many socio-economic sectors, but also as climate change indicators. in this study, the behavior of extreme events is investigated using extreme climate index software (ecis) package. the trend analysis of extreme indices is applied to daily series of tem...

one of the effects of climate change is the possible increase in both frequency and intensity of extreme weather events. extreme weather and climate events have a major impact on ecosystems and human society due to their severity and the fact that they often occur unexpectedly. in warmer climates and during transition seasons, cold extremes have agricultural impacts that are manifested in the d...

in this paper, presenting two simple methods for ranking of efficient dmus in dea models that included to add one virtual dmu as ideal dmu and is using the additive model. note that, we use an ideal point just for comparing efficient dmus with. although these methods are simple, they have ability for ranking all efficient dmus, extreme points and the others, also they are capable of ranking the...

this article will address the extension of super efficiency method to rank the non-extreme efficient decision making units. many methodologies have introduced methods that can rank efficient units, amongst which, the super efficiency method due to its ability to provide meaningful geometrical as well as economic analyses has a significant place. but the common problem with all the super efficie...

Maximum margin clustering (MMC) is a newly proposed clustering method, which extends large margin computation of support vector machine (SVM) to unsupervised learning. But in nonlinear cases, time complexity is still high. Since extreme learning machine (ELM) has achieved similar generalization performance at much faster learning speed than traditional SVM and LS-SVM, we propose an extreme maxi...