In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …

This paper aims to provide a comprehensive review of nature-inspired techniques used in
image segmentation problems. We focus particularly on multi-objective clustering and …

Land use/cover classification is one of the most important applications in remote sensing.
However, map** accurate land use/cover spatial distribution is a challenge, particularly in …

We contend that corruption must be detected as soon as possible so that corrective and
preventive measures may be taken. Thus, we develop an early warning system based on a …

The combination of multiple classifiers, commonly referred to as a classifier ensemble, has
previously demonstrated the ability to improve classification accuracy in many application …

Purpose This paper aims to assess the application of seven statistical and data mining
techniques to second-stage data envelopment analysis (DEA) for bank performance …

In this paper, we study the problem of learning from concept drifting data streams with noise,
where samples in a data stream may be mislabeled or contain erroneous values. Our …

Stroke refers to a spectrum of clinical manifestations with underlying neurological
dysfunctions of the brain. It is a medical condition which is often misdiagnosed and …

An ensemble is a collective decision-making system which applies a strategy to combine the
predictions of learned classifiers to generate its prediction of new instances. Early research …

Effective decision-making techniques are essentially dependent on the capacity to balance
(symmetry) requirements and their fulfilment, that is, the capacity to accurately identify a …