A Simple Data-Driven Level Finding Method of Many-Electron Atoms and Heavy Nuclei based on Statistical Outlier Detection

Finding Outlier DMUs in Data Envelopment Analysis

A statistical test for outlier identification in data envelopment analysis

In the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. In these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. This paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. In the prese...

Many- Electron Harmonium Atoms

A novel method for detecting structural damage based on data-driven and similarity-based techniques under environmental and operational changes

The applications of time series modeling and statistical similarity methods to structural health monitoring (SHM) provide promising and capable approaches to structural damage detection. The main aim of this article is to propose an efficient univariate similarity method named as Kullback similarity (KS) for identifying the location of damage and estimating the level of damage severity. An impr...

A simple and effective outlier detection algorithm for categorical data

Outlier detection is an important data mining task that has attracted substantial attention within diverse research communities and the areas of application. By now, many techniques have been developed to detect outliers. However, most existing research focus on numerical data. And they can not directly apply to categorical data because of the difficulty of defining a meaningful similarity meas...