recently different approaches have been developed in the field of sensor fault diagnostics based on auto-associative neural network (aann). in this paper we present a novel algorithm called self reconstructing auto-associative neural network (s-aann) which is able to detect and isolate single faulty sensor via reconstruction. we have also extended the algorithm to be applicable in multiple faul...

k-means has recently been recognized as one of the best algorithms for clustering unsupervised data. Since k-means depends mainly on distance calculation between all data points and the centers, the time cost will be high when the size of the dataset is large (for example more than 500millions of points). We propose a two stage algorithm to reduce the time cost of distance calculation for huge ...

Multiple comparison methods (MCMs) are used to investigate differences between pairs of population means or, more generally, between subsets of population means using sample data. Although several such methods are commonly available in statistical software packages, users may be poorly informed about the appropriate method(s) to use and/or the correct way to interpret the results. This paper cl...